It strikes me that if their models were good enough for recursive self improvement, then the VCs would have pushed to delay IPO until such time that they had clear market dominance.
For some reason they need the $100B today at the cost of dilution, rather than additional private rounds and/or using cashflow+profits to continue the advancement.
As has been said many times, this is not a normal IPO meant to raise funds for a growing company. This is a liquidity/exit event to let investors, founders and employees realize paper gains.
It hard to say they are doing this now because they need the money now - they are committed to spending close to $1T ($1000B) on datacenters/etc, and the IPO will only raise them around $50B (5% of what they need).
The timing seems more decided by the fact that growth may never look better than it does now as tokenmaxxing gives way to customers looking for ROI and cheaper alternatives to frontier LLMs, such as decision models and non-frontier LLMs which are rapidly becoming good enough for many use cases.
I'm pretty sure this is exactly the point maerF0x0 was trying to make without being bland enough to just say it outright.
To your second point, it's been commonly theorized that this is the real reason based on how they have tried so hard to emphasize a specific 6 month period for revenue while it immediately started taking a nose-dive from large companies doing a 180 on tokenmaxxing after that short period.
That claim seems surprising to me, since I'm pretty sure their bonds yield less than 47%.
https://en.sedaily.com/world/2026/10/19/anthropic-offers-10-... says, "According to the Financial Times on Thursday, Blackstone was offered a return of more than 10% on subordinated investment in a $60 billion financing designed to secure Google TPUs for Anthropic [...] The double-digit return is a striking concession given that four months ago Anthropic issued about $4.4 billion of debt at 8.5% in a similar deal known as "Project Big Sky."," so we can estimate 10.5%. 8.5% is already well into junk-bond territory.
If Anthropic were to have to pay a double-junk-bond-level 15% yield to borrow the 1 trillion [US?] dollars that HarHarVeryFunny says they need, they'd need US$150 billion per year in revenues to service that debt. At 47% growth per year, they would reach that level around Q3 02031. That seems like a relatively unambitious timeline to build out the envisioned trillion dollars' worth of data centers and incur that debt.
I think this is an overly negative take. The IPO is mostly primary issuance and the cash goes to the company. This extends Anthropic's runway into years rather than months. Crucially, this means revenue growth does not need to reaccelerate and can be allowed to slow to something resembling a healthy technology company.
The IPO has to happen ASAP because financial conditions are deteriorating for Anthropic and private capital has tapped out. They will need cash, they're out of people to get it from, and the cost to get it goes up every day.
I agree the fundamental question of whether Anthropic can grow past its fixed commitments is still a big unanswered question and that there are a lot of fundamental headwinds that you correctly brought up. But at least the IPO takes the business as it exists today seriously.
An IPO can be one of two things and it all depends on who knows what: a way to raise cash to fuel future expansion or a way to offload a lot of the risk onto people who have no knowledge about what is really going on behind the official filings. It could be both but that's unlikely and given that this is Anthropic who are already in my 'untrustworthy' book I am betting on the second. There will be something that they can legitimately claim was 'unforeseen' and then maybe the stock will substantially drop past the lock-up period. Unforeseen could range from 'oh look, our growth stagnated, who could have predicted that?' to 'Oh, look, those models we warned you against are eating our lunch' and many others besides.
This is a bubble, the question is whether it will fill out fast enough not to implode, taking earlier bubbles into account I don't think it will, and if it does it will wreck the economy and then it will still implode, only a bit later.
Sketch me a scenario please where they can grow a couple of orders of magnitude and the rest of the economy survives?
The lore is that Ford created the assembly line and paid his people wages high enough that they could afford the product they were making and effectively jumpstarted a massive upgrade in welfare. This is the exact opposite.
Their balance sheets look as good as they will for awhile and they are still the dominate player. So it is the window to IPO. Beyond a couple of years from now who knows. But if they want to IPO now is the time.
If you thought there's a 60% chance of it happening in the next year, you would anticipate it, and likely talk about it, but also not want to go bankrupt in the other 40% of cases. RSI doesn't mean instant infinite money, either.
> their "public benefit" plans have always involved trying to share the upside with the public before it goes "exponential"
LOL. Apparently they haven’t seen the chart put out by their own captured safety org, METR, showing that marginal capability per billion dollars spent is plateauing. There will be no exponential anything.
The METR report said that their rate of improvement has accelerated this year, and that it wasn't from throwing more GPUs at research. There's definitely unknowns here and their R&D spend went up, but note that the benefits of a linear improvement aren't necessarily linear, as you cross thresholds.
If you're worried about competitiveness, note that if R&D costs go up, it can sometimes hurt the mid-tier competitors more than the leaders, as it requires a bigger investment to catch up. Chip fabbing economics became worse in R&D spend and we ended up with (almost) only one firm with the scale. No idea if this will apply to AI though.
I don't know what the technical definition of RSI is, but I think AI needs a good feedback loop for improvement rather than just "thinking" about things in isolation.
I've never seen it solve a problem by "thinking harder", but as soon as I give it access to a feedback loop where it has control it can solve a lot of problems, It sort of feels like brute force, but it's not because it's informed about what it focuses on.
theory > change > test > assess > rollback and retry)
It's the same thing I do, but at machine speed. I had Claude Code help me figure out a sysadmin type problem in about 15-20m one day and I don't think I could have done it on my own in a day.
I think the bigger issue is how you convince people to give those findings back to the system. Either you lie about what you're training on or you have to give people a stake in the benefits. For example, I still needed some level of expertise to track down my issue, so why should I publish that so Anthropic can train the next model on it and rent the knowledge back to me?
I guess you're hinting at the difference between model training (including RLHF etc) and models interacting with code, and improving on that.
I guess the real scenario is "simply" a coding agent pointed at code that integrates collected data, likely with the training code using distributed compute. And distributing the training input improvements is surely also already a solved problem, just maybe not OSS.
I don't see why that's an issue? It doesn't really matter if a very large fraction of knowledge workers aren't convinced. They only need a few of the tens of thousands of people who do your job (often better than you), and your knowledge is available for rent.
They probably won't even need to pay them. They'll just make a useful tool in the domains they're focused on, hand it out to a bunch of freelancers and corporates at a discount, and keep it easy enough to teach the agents knowledge work that simply having better agents is sufficient "stake" for people.
They'll call it something beginning with C - for some reason software engineers trust anything that starts with C. Claude Code, or Copilot, or Codex. Something like that.
Because time and capital matter. If you have a model that is 20% better(say more compute efficient) but also have 50% less compute than a competitor: you lose.
Even if you believe they don't need "Wall Street", having a large number of people owning shares and a stake in the future of the company would be beneficial to Anthropic.
> Even if you believe they don't need "Wall Street", having a large number of people owning shares and a stake in the future of the company would be beneficial to Anthropic.
Ummm... why? This doesn't really make sense. Let's see their current investors:
Google (at least 5%), Amazon (at least 5%), Microsoft, Nvidia, Sequoia Capital, Altimeter Capital, Coatue, Dragoneer, GIC, and ICONIQ.
All of those combined have more economic power (and likely more political power) than most countries in the world.
I’m just so tired of the false altruism of startup culture. This is such a real impactful tool on me professionally and personally that I have never been, I can’t ignore, how disgusted I am. This is the same old playbook, the same old profit taking. It’s a shame.
IMO, this is anthropic conceding they can’t go any further and exiting. Actions always speak louder than words. If RSI was coming, you would be able to secure funding and continue developing independently. There must be nothing evident.
they still need many billions in compute, while it is not clear if RSI will provide strong revenue gain, so they propose Wall Street to take part in gamble.
They don't. Show me a company in that was founded in the last 10 years and IPO'd after 5.
VC can wait next 5 years. There are 2 options: they need more capital and can't find it in private markets OR investors think their positions are too risk and want to "derisk"
Just as not every monotonically increasing function diverges to infinity, Recursive Self Improvement doesn't necessarily lead to ASI or whatever they're calling it these days. In fact, you could argue the exact opposite: that RSI might actually show how far LLMs really are from AGI/ASI.
> Just as not every monotonically increasing function diverges to infinity, Recursive Self Improvement doesn't necessarily lead to ASI
It is disappointing just how little recognition there is of this point. For some reason, AI maximalists settled on an exponential model of growth in their mind, and I've yet to see one seriously consider whether RSI might not be that. It's a conversation ender, like bringing up an alternative axiom that cannot be debated, rather than a testable hypothesis.
I agree that exponential growth in particular is debatable, but if intelligence doesn't diverge to infinity then it must have an upper bound, which doesn't seem very believable. Intuitively, it should always be possible to add one more processing unit to increase your intelligence (however it is measured) by a fixed amount. So I don't think it can be below linear.
Hey, I appreciate your interest in the conversation!
> Intuitively, it should always be possible to add one more processing unit to increase your intelligence (however it is measured) by a fixed amount.
That's reasonable. The question is how much return you get on your investment, and whether there are "diminishing returns" or "economies of scale" for IQ-per-dollar.
> I agree that exponential growth in particular is debatable, but if intelligence doesn't diverge to infinity then it must have an upper bound, which doesn't seem very believable ... I don't think it can be below linear.
Being able to always increase your intelligence by some amount, at some cost, is compatible with any of "fixed upper bound" (e.g. exponential decay), "sublinear unbounded growth" (e.g. logarithmic), "linear growth," or "superlinear growth" (e.g. exponential growth). Sublinear growth and diminishing returns certainly seem consistent with every self-optimizing system we've seen so far, including agentic AI.
Any chance your odds were less than 100%, it would be worth the risk because the hype is there. You set the stage, everyone is on the edge of their seats, then you sell out. Prices will be based on your future performance. Leave the risk with the investors. Maybe you keep some in the back pocket just in case you take over the world
probably because even without true, no human in the loop RSI hardware expenditure and power requirements are currently higher than the entire capacity of earth if we did literally nothing other than support AI
Though the truest of true believers also see themselves as one day eliminating scarcity as a concept so it might just be that profit doesn't motivate them.
It's either Wall Street, the government, or something else. Public shares are the current easiest way to spread value to the people en masse, more so if you donate shares to the kids like Michael Dell.
So we are at the point where RSI is happening, but the idea that RSI leads to exponentially fast growth and SI is based on a number of unproven factors, most importantly that intelligence is scalable significantly beyond human levels. We are also not sure of the limitations of LLMs, how it relates to our own intelligence, and how hard it will be to make the jump to other models.
But when it comes to Anthropic, I am almost certain that it does not make sense to argue based on the typical arguments on maximizing profits. Everything I know about the people working there suggests that they are not primarily motivated by money, but by their mission. I bet they would prefer a lower-strings attached private offering, but have no issue with diluting their own stock, if they think it will serve to move Anthropic further ahead on bringing about aligned AGI. Basically, the diluted money will just be missed donations to EA causes for the most part anyway.
When you have AI models autonomously self-improve, you implicitly lose your understanding of how they work and accordingly your supposed control of them?
AI can be a "tool", but only so long as you understand how it works and what the implications of its use are. Being an enormously powerful tool implies, the consequences of not understanding and not knowing are proportionally enormous as well.
Currently, LLMs are used practically exclusively by "professionals" who, more or less, know what they're doing. The idea of applying them "everywhere" completely misses the gap in understanding and responsibility for the vast majority.
I've often heard skeptics say AI enthusiasts think they are building a god but I've never seen any evidence. Are there any quotes implying Anthropic think they are building a god?
> I've often heard skeptics say AI enthusiasts think they are building a god but I've never seen any evidence. Are there any quotes implying Anthropic think they are building a god?
Not Anthropic specifically, but there's this thing that I recently read:
> A.I. company leaders often talk about how their work might lead to human extinction soon. This is astonishing. Even if you wanted to destroy humanity, you wouldn’t say so. If, however, you wanted to save the human species, wouldn’t you stop developing this technology?
> There is an explanation for why some tech leaders, so seemingly worried about an extinction-level event, are plunging ahead with A.I. development: Mankind’s survival, while important to many of them, is less critical than building something they believe to be not only conscious but godlike. A substantial portion of the A.I. community, in celebrating this belief, is quick to support any action or statement that reinforces the idea that the technology is like a deity. They might call for regulation, but only in specific ways — perhaps by deploying more A.I. to control A.I. — that adore the technology’s powers. It is that adoration that is nonnegotiable.
It's by the guy who apparently invented VR and was apparently mentored by Marvin Minsky. So he likely has the kind of access that gives his opinions credibility.
> Thanks, although that still sounds a bit like a skeptical viewpoint.
I think it's unlikely that an AI enthusiasts would literally claim "they are building a god," but such an attitude (or something very similar) is implied by their statements and attitudes, e.g.
1. Talk/hope of building something that so exceeds human capability, it's beyond human comprehension and control.
2. Taking existential risks for humanity (by their own statements) to try to get there, against all reason.
I guess. Anthropic's about page is more "We aim to build frontier AI systems that are reliable, interpretable, and steerable".
I guess they think AI will become smarter than people but I'm not sure that's a god. I've always thought of gods as the dictionary "a supreme being, creator, or a supernatural entity" rather than a souped up chess computer.
> I guess. Anthropic's about page is more "We aim to build frontier AI systems that are reliable, interpretable, and steerable".
That's a marketing page. It sounds like their view is more like "we're building a god, but only we can be trusted to make a good god instead of a devil."
> These schools of thought fused for Dr. Amodei into an unyielding conviction that A.I. could be so dangerous that only he and like-minded technologists could be entrusted with building it. That catalyzed his stated efforts to create A.I. before people without concerns about the safety of humanity did, and spurred a desire to control the technology, his friends and colleagues said.
> I guess they think AI will become smarter than people but I'm not sure that's a god. I've always thought of gods as the dictionary "a supreme being, creator, or a supernatural entity" rather than a souped up chess computer.
We'll seeing God as "a supreme being, creator" is only a particular conception of god. IIRC, polytheists often gods as just powerful supernatural entities that are owed deference (because otherwise they might cause you trouble).
> or a supernatural entity" rather than a souped up chess computer
Obviously a AI machine god would fail a "being supernatural" test, but I'm sure the thinking goes that a super-intelligent AI would be so powerful, it's natural-ness wouldn't matter
All they did was build a really good software engineering tool, and that’s gonna be when the bubble pops, when you realize you really can’t commit it to handling any real workflows, and the slop that people are creating, vibe coding, that have never touched code in their lives.
Can you give an example of people who worshiped a false god and of what happened to them? Because I am honestly at a loss. I am not even sure what a false god is and what the difference is with a true one.
Don't you have one already? What improvement would that artificial one be and to whom?
Anthropic desribes itself as a "public benefit corporation" in its IPO. The irony. Or is it sarcasm?
A god isn't your subordinate. You cannot "program" your wishes into it, like a genie/jinn. They (or their investors) want to make themselves into gods. Over you.
The domains where they apply it, privately for instance, aren't of immediate import. Their fuck-ups stay local.
The consequences of "AI use" are manifold and very poorly understood. That doesn't make them less impactful, on the contrary.
Whether you look at "humanoid robots" or incorporeal LLMs, when they are more capable than yourself, you become their dependent counterpart, not their "master".
> When you have AI models autonomously self-improve, you implicitly lose your understanding of how they work and accordingly your supposed control of them?
This was always the case with ML, even absent RSI. Big bag of weights is a pain to figure out exactly why it can do whatever it is that it does, leading to all kinds of blind spots about how they go wrong.
> Currently, LLMs are used practically exclusively by "professionals" who, more or less, know what they're doing.
He distinguishes between weak recursion (using sotfware to build more software), and strong recursion (handing over model development to AI which does everything), and makes a pretty strong case for the fact that only weak recursion is happening.
This maps to my experience with AI models, they reduce the cost of experimentation massively, but they can't (currently) design experiments themselves.
Even then, training RL is very data hungry, and most profitable tasks don't have good data so even if we got superintelligence (whatever that means), it's entirely possible that progress would still be bottlenecked by lack of high quality training data.
> Theres also the idea of LLMs producing synthetic data to contribute to new models. Perhaps that is not as effective as hoped.
Wasn't model collapse/model decay a big issue since the beginning? i know that RL kinda mitigate the effect, but if this was close to not be an issue anymore, wouldn't we have a paper on that already? All that i've seen on the subject was about mitigation, never about solving the issue.
Sorry if my question is dumb, I need to do some research about the difference between image generator and text generator, i feel like my understanding of LLM is skewed by my usage and understanding of Z-turbo, but i only have that much time in my week.
It works because artificial neural nets take a lot of examples of something to learn it (way more than natural neural nets). So at the simplest level it's just copying items in the training data enough that they become salient.
More complex synthetic data generates things that could be in the training data but aren't for some reason. For example, machine translation training corpuses often contain a lot of formal language (because formal documents are the ones that get translated), so you might generate a bunch of casual conversation to improve the translation model's ability to handle that.
> Everything I know about the people working there suggests that they are not primarily motivated by money, but by their mission.
And what is that mission?
I'd almost prefer it if they were motivated by money, then at least we know what we're in for. All this 'mission' stuff seems to effectively amount to 'we're saving the planet, sorry you got in our way'.
Are we really entertaining that 2010’s “it’s about the mission to make the world a better place, not the money” dross again? You can see this nonsense parodied in literally the first episode of Silicon Valley
Apple, Amazon, Intel, Google, NVIDIA and Tesla all had world-changing product before their IPOs but they didn't stay private until clear market dominance.
Because private rounds still dilute you.
And VCs tap out well before $100B.
And they'll need more than $100B to accelerate widespread economic diffusion.
And RSI can't hallucinate gigawatt power plants and TSMC fabs into existence.
> Apple, Amazon, Intel, and NVIDIA didn't stay private until clear market dominance either.
Apple, Amazon, Intel, and NVIDIA all went public in an entirely different world, before the JOBS act.
I'm not necessarily taking the same position as the person you are replying to, but using these companies' IPOs as comparisons for what Anthropic is doing is not exactly Apples to Apples as it were.
Why not? Win the stock market, break ECC and own the internet. There are many ways to make infinite money if you have infinite intelligence but not infrastructure. True RSI wouldn't announce itself
Even if that were true (i.e. the models were good enough for infinite recursive self-improvement), the risk is still rapidly increasing with time. I presume most VC's would rather take the current exit with their pants intact.
Commoditization is coming and faster than they had expected. That's why the push to IPO now. Delay another six months and their $1.3T IPO could be half that.
Kind of hard to believe in recursive self improvement, every time I tried setting an LLM to loop on itself to "recursively" improve code towards a goal it always descends into utter garbage. I think the main challenge is probably knowing exactly what you want to get, and then having a training landscape that is smooth enough so you can climb there? I guess these models can probably iterate their architecture to max out existing benchmarks but at some point they will essentially just do p-hacking as the model that improves the model will invariably leak the validation data into the training process on the meta level, or so I would assume. And if your goal is to create a model that can compete with human intelligence in math then how would you even come up with a scoring function for that, will you let the model do multiple years of fundamental math research and then see if it produces something that is novel and interesting? And how do you score if it's like 99 % there, 50 % or 10 %? From my naive understanding that's probably the main challenge, these models can only optimize if you have a clear measurement of goal achievement that can be climbed to, if there's only a very far fetced goal without clear intermediate success states I don't see how the current generation of models should get there.
> ...every time I tried setting an LLM to loop on itself to "recursively" improve code towards a goal it always descends into utter garbage.
I've had this just today with both Fable 5.2 and Astra. It was an extremely simple task too, basically just "Here's the extremely detailed ticket (a large ticket, but extremely well documented, one of those tickets where even an intern new to the team could just follow along and get it done in a reasonable timeframe despite the size), here's the MR, let's make sure that we trim some of the fat in this MR from all the iterations we did on this ticket over the last month it's been in review". Both models shat themselves monumentally, started changing random crap all over the place, and in the end this exercise in removing some code only ended up adding a LOT more useless code that was doing fucking nothing, not to mention how unreadable and low quality it all was.
Time and time again, my actual real-world experiences with this tooling is a "meh" at its very best. We have all the harnesses and MCPs and all the other bullshit the AI bros like to shove on you, good CLI tooling, sandboxed environments, basically unlimited access to SotA models, excellent human-written documentation for the context, a mature, stable and battle-tested CI environment which makes changes extremely easy to test. Anything other than the most simple possible translation tasks, and none of these tools ever actually save any time whatsoever.
Every fucking time it's just introducing 3 billion useless unit tests that assert x == x despite who knows how many instructions in the "harness" detailing in excruciating detail how to write tests. Or it's introducing incomprehensible garbage comments that leave you more confused than if there weren't a comment to begin with, or the infinite other plethora of rancid bullshit this tooling leaves behind
They need the money to have a chance of getting to RSI, and $100B is hard for private rounds to realistically supply. An IPO also lets VCs show real returns to their LPs instead of paper markups. This then helps VCs raise larger funds for later investments
Log expectation says to pick 99% of 200M. You should bring it down to 73%.
This doesn't account for what you could get with 50M in the 5 years span though. I have no good model of that.
"Market dominance" isn't the right metric. VC's want maximum price at the moment of lockup expiration. With so much uncertainty, it's smart to eye the exit and have the option to take gains.
> It strikes me that if their models were good enough for recursive self improvement
I just can't imagine this is true when their overreach problem (doing more than you ask), hallucination problem (lying), redefinition problem (doing something completely orthogonal to what you asked), and harm problem (doing something that is exactly the opposite of what you asked) are all far too high at this point, and by most measures - all of the recent models are worse on most (or all) of these metrics.
They are giving up here in RLHF to benchmaxx the metrics people are looking at to pretend like they're making huge gains, when they're largely running in circles.
They are getting better at pass@1 at the expense of far worse p90s on real agentic tasks.
> For some reason they need the $100B today at the cost of dilution...
You can do the math on the dilution, which will be on the order of ~10%, give or take. If the new shares are worth more than existing shareholders paid for theirs, each share can be worth more even though the percentage is smaller.
Couldn't the additional liquidity and funding provided in an IPO make the difference of who gets to RSI first? If there's only one winner, being a close second while staying undiluted might still be a worse outcome.
It makes zero sense. Even if the model can self-improve it doesn't mean the hardware need will go to zero immediately. Human society as a whole is a self-improving system (at least in terms of technology) and it doesn't mean humans consume less and less resources.
They need resources and $100B can buy them that. I don't think you need a conspiracy theory to explain that.
The whole idea of self-improving machine equals immediate singularity is just wrong and ridiculous. I don't know why so many people are attached to this idea. Perhaps just because "singularity" is such a cool sci-fi word?
Chip fabs take many years to build, and that can't be accelerated with intelligence alone. Much of it is limited by physics and practicality, such as having to do the steps in sequence. You can't "align" the ASML machines until the foundation concrete has set!
Yeah, but given a medium that leverages nitrogen vacancy centers for phonon propagation, you can replace photolithography with ... I dunno, but maybe the God-in-a-box does.
What semi-supervised learning tells us is that any system with no humans in the loop will at some point reach a limit, and require more supervised data.
Deep learning had no humans in the loop, but there's always a bigger outer loop with a human somewhere.
They all knew about the stuff that is coming out now (Jensen stepping down due to chinese spy stuff) and has been out and debated for a while now (circular financing) and money drying up as a result. Winter is coming...
Comment from a perma bear. So take it with a grain of salt. lol
Yeah they’re completely stumped. They stole the idea for LLMs from other people and have now hit the limit of that idea. They’re spending a billion on payroll and none of their people have a clue what they are doing.
I don't think recursive self improvement will lead to a sudden takeoff. It initially probably won't be much better than human assisted improvement that's going on now and still constrained by compute available.
Once you have a super-intelligent system, of course you want to scale it up. Remember, Amodei's goal is "countries of geniuses" in data centers. Super-intelligence can't just think those data centers into existence.
This seems like a reach. Just because Anthropic could theoretically become a future infinite money printer, that doesn’t stop it from needing money in the interim.
It also doesn’t stop investors from being happy liquidating at an already good return, especially since they can choose to liquidate partially.
Simplest possible answer is A: they are dramatically ahead right now, and B: there is not nearly that much privately held money available for relatively risky investments.
Based on METR's evaluations of their unreleased models, they don't seem to be dramatically ahead. Actually, it seems that each iteration brings smaller performance gains than the previous ones.
EDIT: Maybe before downvoting read the actual evaluations?
Lmfao, it takes some real balls to post a chart showing their performance growth over the last year is speeding up and conclude it's bad.
The gains between generations are smaller because model releases occur more frequently (this is primarily driven by them taking more frequent snapshots of the base model during training).
The title of your chart is literally: "As of October 2026, benchmark scores appear to be increasing at 1.9x their pre-October 2025 rate [95% CI 1.5x-2.8x] - when including recent internal models."
And once all those engineers cash out, China will become dramatically ahead because they are only a month behind already and can pay way better than the IPO
So much of "dramatically ahead" is due to the Claude Code harness being better than anyone else's.
Fable is great, certainly, but it's no better at writing or reviewing code than the top-end Carbon or Astra models. To the extent Anthropic has a moat, it's Claude Code. Obviously that's not much of a moat, but their competitors seem content to camp on the other side of the drawbridge for some reason.
What makes it a moat? How did you compare? I don't think CC has particularly outstanding integration (used in practice) or performance. People use it because Anthropic shoves it down their throats, making it risky to use anything else with their subscriptions, and generally gatekeeps their models like crazy.
I use all three major harnesses regularly (Antigravity, Codex, and CC) and CC is better. It gets used for writing code, while the others are used only for reviewing what Claude writes.
Codex is pretty close in a lot of ways, as the other poster says, but Astra consumes tokens at a higher rate, and when it compacts it completely lobotomizes itself. That used to be a problem in Claude Code as well, but it has been largely solved (although at the cost of making the compaction take much longer.)
Antigravity reminds me of the old comic strip where Firefox and Chrome are duking it out, while Internet Explorer is sitting in the corner wearing a helmet and eating out of a jar of paste.
I don't see in your reply that you attempted to decouple models from harnesses, it seems you're mixing them up. I regularly test different harnesses on different models and for my use cases CC is just about as performant as OMP with Claude, for example, but it takes a lot more tokens. I don't see anything special about the harness itself, that's why I'm asking about actual comparisons.
I don't see in your reply that you attempted to decouple models from harnesses, it seems you're mixing them up.
Normally I run the models that the harness is intended to support. You can't run Claude models anywhere else besides Anthropic's own CLI and desktop harnesses -- or at least you're not supposed to -- without paying out the nose for API tokens.
I do use DeepSeek 4.1 Flash 1017 in Claude Code when I want an abliterated model for security-related work or unhobbled browser control, though. I know it's possible to get OpenAI models working in CC, but I haven't bothered. Gemini I'm not sure about.
I mean, OpenAI has codex? I find it pretty equivalent. So they are trying to equalize. (Less said about Google CLI attempts the better). And there’s definitely not model equality - Astra was a big step forward but generally loses on daily utility to opus 5.5, much less fable. I would be very scared for Anthropic if it was trying to compete purely on harness; I suspect most of its usage is by default because the models are better. In the pre 5.5 phase I saw a lot of migration to codex/pi, and I’d be fine without CC as a harness today.
Exit liquidity? I feel like it would be a lot easier to raise $100b from a few private investors if you had reason to be confident that you were gonna make a self-improving cash printer. If, however, you weren't sure what you were gonna actually be able to pull off and saw a plateau or drop coming you could use an IPO to generate hype and get some liquid cash and then dump your position on retail and institutional investors if it doesn't work out. Why don't they don't rely on private investment and profits? I don't have the information to verify this for sure but one theory is that they don't think there will be much more private investment or cash flow.
I mean there's only so much money you can raise from private equity. It's entirely possible they've achieved some big breakthrough but need more money to distribute it than private equity can supply. That said I'm not sure they need another breakthrough to justify the stock price, just gradual improvement and user growth
If you need 10x the available compute you’re not going to get it for 10x what you already paid. You’re talking about potentially destroying all of your vendors.
If you’ve ever don’t consulting work, you know how dangerous it is when the majority of your revenue comes from a single customer. You stop being independent, you stop having your own set of values, and if anything happens to that company, you’ve already proven you lack the ability to court as large a contract from other customers.
It always ends in a loss of identity and huge layoffs.
Making vendors product triple their current production rate for the next five years isn’t even possible to start this year, because they have to build facilities and train employees. Nobody runs businesses at 50% capacity anymore. That’s considered wasteful, even stealing profits from your shareholders.
They can’t even get memory chip companies on board with their koolaid.
> For some reason they need the $100B today at the cost of dilution, rather than additional private rounds and/or using cashflow+profits to continue the advancement.
Both Anthropic and OpenAI seem to be burning cash as if it was a game of startup chicken. Of course they all desperately need cash.
There is a lot of value from LLMs but it is something that I can switch easily. Yes, some frontier models are much better but users can still chose to use cheaper models for most of the work. In fact most applications, through which people will interact with LLMs anyway, will not need frontier models unless they offer "chat with AI". Anything that solves specific problems (even multiple problems) does not need frontier LLMs.
Anthropic and OpenAI will have to become more of the end user application stack. Files, calendars, emails, photos, and much more have to pass through them for them to keep making money. Else they cannot make money like the way they have been in this early era of LLMs.
Switching models is easy as a solo developer. Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc. I think Anthropic will look a lot more like a cloud provider like AWS or GCP. Same-looking product, very high switching cost that would have to be driven at the CIO-level because of all the integrations that have to be redone, IP concerns etc. And ultimately they are selling compute capacity.
Edit: I should clarify that I don’t think this justifies their valuation. It puts them in competition with much more entrenched players with established customer bases, and who aren’t in massive debt to provide their compute. I’d also like to distinguish between a model provider as someone who provides weights vs a model provider who connects their GPUs and models to your codebase and internal systems - I think the latter is where the sustainable business is.
Incidentally this is why I still feel Google is well-positioned in the long-term AI race. If they can remove their head from their ahh and make a coherent product offering across Workspace, GCP and Gemini, they could become as entrenched as MS.
I would assume AWS is probably the most interested in acquiring Anthropic out of the three major cloud providers.
> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc
I don't think this is entirely true. Companies are deploying open-source LLM gateways to be able to do that very easily now. Today, you can switch Claude CLI to any model besides Anthropic via https://github.com/BerriAI/litellm and there are major companies doing that.
This works with your favourite ADEs such as Orca as well so I disagree with this premise. The whole experience of switching is pretty seemless based on personal experience.
We saw this play out in the cloud era, notably with OpenStack. Even through the core abstractions (chat for LLMs, compute and storage for clouds) can be almost perfectly abstracted over, providers will race to add niche, enterprise-y features that are harder and harder to put behind a gateway or proxy. Those features aren't the core value of the platform but they are important enough to create lock in.
When I write a system against a particular cloud storage API, I end up implicitly depending on a bunch of deterministic subtleties of exactly how this storage API works.
AI is already so non-deterministic and fuzzy, I'm not sure the same issues apply.
Agreed, deploying AI gateways has become extremely common in enterprise settings. A lot of admins think they are going to use it for guardrails, but I think the real value is in centralized cost tracking and ability to (relatively) seamlessly aggregate providers.
We have like a dozen different LLM tools available to us and it's as easy as clicking on a dropdown to switch in every single one of them, and we have several thousand employees. Self-hosting with the cheaper OSS models is also becoming more and more attractive for larger orgs.
That's just inference. Claude.ai is a platform that enterprise IT teams connect up to all kinds of other applications, and gets use beyond the claude code CLI. Non-developers get used to this functionality - whether it's their form-building stuff, artifacts, slides/presentations, etc... they're building an offering far beyond just inference. I agree the latter is a commodity now, though companies will compete on privacy options (ZDR, guaranteed confidentiality, etc)
Many large enterprises don't use Claude.ai. All their traffic goes through an internal gateway that routes to Bedrock. In addition, there is a whole ecosystem of LLM related infrastructure/tools deployed by "enterprise IT teams" where Anthropic barely has any presence.
But many do, so price them according to that. This is like saying "my office doesn't use Microsoft". Sure, lots don't. Lots do, no one is questioning that Microsoft has a very viable long-term market there.
For infra sure, but its dominance in other areas is quickly eroding. My org is super heavy Microsoft/Azure and we have all of their tools. Everyone making anything useful is using Claude + Databricks because it is a better experience for both builders and users by every measure and it isn't even a remotely close competition. Power BI and Copilot are a total wasteland. The only Microsoft program with any staying power is Excel.
> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc
Once the cost reaches a threshold, everything is doable. We ditched Datadog in less than a month. Someone I know had their company ditch slack in a quarter and google cloud usage of 100+ million in two. Everything is doable.
I already mentioned the timelines. Cost is a beautiful line item in your balance sheet that can get things done pretty quickly, especially when it’s as big as AI. It took less than 2 quarters for us to go from “hey use ai in everything or get fired” to “hey we’re putting in default limits that are intentionally very low, if you need more, you’re going to need approvals”.
The stickiness of AI as a whole, let alone a specific provider is not that high as people are making it out to be.
Working for a 10k+ corporate and we made it pretty easy to switch to any provider, people here can use Anthropic's, OpenAI's, and our own self-hosted open weight models very easily. It's one drop-down or `/` command away to switch between them.
I think other companies are probably doing the same, the moat of a AWS/GCP/Azure is much deeper with how contrived it is to migrate between them even if you abstract as much as possible with something like Kubernetes.
Vendor lock in is quite well understood, most larger companies (the one's I have worked with anyway) are aware of the risk and take steps to actively avoid it. Once bitten, twice shy.
Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc.
Speaking as someone who has been at professionally this since the 1980s, I suggest that while sometimes switching costs and network effects happen "organically," in this century businesses devote enormous amounts of attention to artificially building switching costs.
It's such a dirty practice that we have a four-letter word for it, a "moat." But of course, the moat isn't really to keep competitors out of a market, it's actually to keep customers trapped within it.
I fully expect every one of these AI providers to put as much work into trying to trap their customers within their ecosystem that they do to improve their capabilities.
Since siege warfare is about bringing down the fortifications and a moat is part of those fortifications, cyber siege may be something akin to patent trolling or IP copyrights? Fire off dozens or hundreds of claims against your target and drown them in legal costs.
Then you have the experience to know that every land grab in technology so far has followed the same enshittification path: At first it's all about competing with other entrants to provide value and win customers. Then, inexorably, it shifts from winning customers to defending their turf. Then, inexorably, it shifts from protecting turf to maximizing extraction from their turf.
If you believe that this will be different, why not? But for now, I'm expecting this to go the same way. Yes, LLMs are something completely new. But also, the people behind them are exactly the same as the people behind every previous land grab.
I can't wait for anthropics next big drop to be that it can order you a pizza, steering towards benign, token burning features that you didn't ask for and eye real-estate abuse for ads.
It's the end of an era. Lets pray open weight models give us a real choice soon.
In the meantime, Stonks up Anthropic. I'll always remember the good old days when you championed developers and changed what was possible.
> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc.
I'm not so sure about this. I guess it depends on how well people did their job there.
Ideally, whatever people built is loosely coupled to that third-party resource, meaning that switching cost will stay low.
After all, it's probably just prompts + an API layer. Unless one micro-optimizes their prompts for claude (which then breaks once a new checkpoint drops, hence is a bad idea regardless), pointing them towards a different API endpoint should be doable.
Currently we are building agentic systems for various business functions like Legal and Finance. How these models perform in those tasks is paramount, and things like cost per run is only a part of the equation. It can become very subjective, and things like brand recognition comes into play. The cost of a counsel or a VP finance overshadows the savings you get by micro-optimizing for a cheaper model. We tend to use the best-in-breed LLM for the various tasks - mainly Claude and Gemini, and sometimes GPT.
> How these models perform in those tasks is paramount,
Then you have no choice but to use your own hosted model because that's the only way you can be sure the model isn't going to be removed or quantized/nerfed behind your back.
If your system can widstand the fluctuations of closed models over time, then it can most likely support switching between multiple providers in the first place.
I should be more clear. The "performance" I'm talking about is not entirely objective in these use-cases, and the bigger part is something you can't reliably measure through tests or evals. The value proposition of the frontier labs is their post-training taste, how reliably the model handles ambiguity and infers intent, while at the same time progressing at the leading edge. Self-hosting trades that for output stability, and absorbing minor drift within one provider is still far easier than switching labs when your workflow and UX are tuned around a specific model's quirks.
> The value proposition of the frontier labs is their post-training taste, how reliably the model handles ambiguity and infers intent,
That's also literally what frontier labs break all the time, be it by removing the model outright (remember the outrage over the forced replacement of GPT4o with GPT5) or by tampering with some configuration (aggressive quantization or whatever bullshit occurs right before new models are released).
If you ever need to scale to millions of customers, then cost per task is paramount. If it’s a one-off vibe coded custom project for one client, then best-in-breed is mandatory without it falling apart.
Ur case actually strength the argument for open weight self hosted model. You would have precision control over not only the technical issues, but also the legal issues.
Once the open weight models are good and cheap enough, there is no reason not to use them
My company switched from direct access with providers to AWS Bedrock. Now we just pick which model we want from the list exposed by Bedrock. We can also leverage tools like T3 which allow hand off from one model to another.
Easy to say, not so easy to actually get your mechanics, your project managers, and your business operations staff to get over that hurdle unless you’re willing to handhold them through the process of changing directories or explaining what an environment variable is to them. (This isn’t just boomers btw. Lots of young people have had the command line abstracted away from them their entire working lives)
There are many perfectly successful companies out there with limited computer literacy among much of their employees, let alone AI literacy. Those companies are great targets for Anthropic’s enterprise sales team, if they can provide an intuitive user interface that allows said employees to make use of AI tools, allowing them to leapfrog the need for computer skills.
We’re not talking about developers, we’re talking about people who just want the technology to let them do their job. What even is AI literacy? 2 years ago it was prompt engineering
Weird take. Tech boomers started with tape or commandline. The ide only became the development environment of choice in the late 90s, firmly with genx and millennials.
Claude code is a terminal interface not a command line tool. More like vim than sed.
Visual BASIC was 1991. QuickBASIC, Borland Turbo Pascal, SmallTalk-80, NeXT InterfaceBuilder, all pre-1990, several well-pre-1990. Boomers absolutely had, and indeed devised, the IDE.
Model switching behavior is going to be far more complicated.
First, everyone and their mom is selling AI now. It is being bundled in nearly every product. Buy CRM to run your company - they will upsell you their bespoke AI - mostly RAG/chatbot using the data inside the platform. This is an important area because today lot of companies are trying to build their own AI bespoke workflows. But companies like SAP, Oracle will spend money on improving this aspect. And people who buy/use AI for this purpose don't care if the underlying AI is Claude or not.
Then there are cloud providers. You can get Claude, OpenAI from AWS Bedrock etc. They will take the heavy lifting of changing integrations, IP concerns etc to keep people on their platform. With time expect them to make it even easier, not harder to switch models. Also, they will push for open source models because it will be more profitable.
Lastly buying from direct providers. This is here the lock in comes in. But I believe fewer and fewer enterprise will buy directly - many preferring to buy against their cloud commitments.
My F500 company switched ~10k employees of Claude to copilot in 30 days. Google did similar between Jetstream and Claude. The moat just isn’t there right now
I really think you overestimate the level of lock in here. If a companies tells the devs to use X because it cost 1/10 of the price they will just have to suck it up and switch.
I didn't particular want to work on a "all in agentic project" but that the nature of being employed.
The same LLM we use day to day will make it trivial to switch out providers in our infrastructure.
One thing that makes easier to switch with LLMs as opposed to other tech is the text-in text-out nature of the LLMs. All specs and data are in text files mostly in natural language which is patent free. This makes it harder to lock in content.
As you have written, the agentic harness is a slightly different matter with plugins and features. But the core tech makes replicating software a lot easier so you can in principle use an agent to make it easier to switch from its own harness. There are caveats to this since in practice the quality and feature sets of harnesses are not the same. But in my opinion, it is far easier to switch agents than switching other tech that came before them that used proprietary formats and apis to lock you in.
> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc. I think Anthropic will look a lot more like a cloud provider like AWS or GCP.
This might be true today because Anthropic/OpenAI/Google have good sales AEs, but as soon as company's start doing FinOps on their LLM spend, the game is over for them. The model will become fungible and hot-swappable (as it already is) and it'll be a race to the bottom.
I think the future will be a lot different they we expect, AI is going to be the infrastructure layer while there will be toolings for each processes, so switching between model is a built-in feature, i.e. the tools will inject specific prompt or context based on the models, and all these are designed by people selling the tools, hence, a moat?
Let's say that the face for largest foundation model slows down enough to make the companies cloud-like, instead of whatever they are mow. Imagine the free credits that OpenAI would consider giving you as long as they are spent on migration out of Anthropic. They could even classify conversations by themselves.
This is the logic behind B2B SaaS's revenue multiples, and yet AI itself is causing those multiples to rerate based on a change in expectations about the durability of an entrenched SaaS provider.
Depending on how the company leverages them, it's super easy.
For us it's as easy as clicking a dropdown. The copilot vs code extension allows for this ez pz, the same is true for companies that implement an AI gateway for other tooling.
Totally agree with your Google thesis. I would never count them out. I say that as someone that uses Claude (and a little chatgpt), but not Google's AI at the moment.
With ad money Google never had to learn how to ship a product that makes money. An obvious place they fail is that when something breaks there's no one to talk to to fix it.
Switching LLM providers as a company is even easier than a solo developer, most large companies I know are using AWS Bedrock and selecting another model is basically just a checkbox for them
As far as I know, our corporate has deals with all of them: Anthropic, OpenAI and GitHub Copilot.
They stroke a great discount deal with all, so different teams/departments have different provider, and those using Copilot are even free to switch between models as they please (although with lower usage limits).
You could make the argument that it's not worth switching SAAS providers for enterprises when the costs were like 10 dollars a month per developer and switchign would require 1 team to work for half a year... but with AI providers it's more like paying 1000 dollars a month per developer vs paying 200 dollars if you strike a good deal with different provider and swtiching costs are more like 4 to 8 hours of work for each developer.
Indeed, and I think AWS is in a perfect position to consolidate the entreprise market rather than Anthropic here, they already have the rest of the server stack so this is just another addition.
I've observed that there are some companies and some folks that are very fanatical about a specific provider. "Only Claude" is very common. "Only GPT" less common, but still see it.
A lot of the non-technical and semi-technical folks are only comfortable using a specific client like the Claude desktop app. A lot of teams wrote skills and eval'd/benchmarked their skills specific to a model family and harness.
The "I can use any model, any harness" or "I only use a meta harness" (Orca, Paseo, Herdr, etc.) crew is relatively small IRL. Most people are still single-session, single platform user mode.
Most orgs have an enterprise contract with a single provider so all of their internal assets are built for the provider. It goes beyond skills, but also the telemetry, enterprise policies, and managed configuration.
For a company though, the idea that a few disgruntled employees will shift massive purchasing decisions is a bit of a stretch.
We have a developer on our team that keeps asking for a claude code enterprise license, we keep telling them "no, it's way too expensive, get used to using the copilot extension/cli".
For consumers, sure, but the bulk of the revenue opportunity is enterprise. Anthropic/OpenAI have a hard row to hoe IMO.
As an only-clauder, there's another elephant in the room. Anthropic is by no means perfect, but:
* using OpenAI supports the Altman/Thiel/Musk/Ellison/Karp/Trump billionaire Orwellian worldview and also ads
* using Grok supports a ketamine-addled open fascist sympathizer jizz-spewing 12-year-old-edginess memelord and his similarly broken worldview
* Google's models are pretty good but every single product they have ever had is ultimately either suborned or killed by the advertising division
* local models pretty much only half-exist because Jensen Huang wanted to cheat on his wife; future is unclear
One can argue for harnesses and so forth being lock-in, but the ultimate lock-in is morality and wanting to have a civilization at the end of all of this; I can't recommend either enough
It’s weird that people don’t seem to get this. LLMs are the most easily switched-out technology I’ve ever used as an engineer. The input is literally just free-form text.
> It’s weird that people don’t seem to get this. LLMs are the most easily switched-out technology I’ve ever used as an engineer. The input is literally just free-form text.
It depends, if you're automating business processes (honestly probably where the money is), then you'll need a really comprehensive set of evals and moniotoring to ensure stuff doesn't break if/when you change providers.
If you have none of that, then switching will be very expensive (but it was ever thus).
> you'll need a really comprehensive set of evals and moniotoring to ensure stuff doesn't break if/when you change providers
Unless your self-hosting open weight models, you need this even if you don't change providers, since you have no control of what's on the other side of the API.
That just means the business automation is not deterministic, and highlights the issue with LLMs. The solution is not to switch providers but instead make the LLMs generate something that is deterministic given the same input.
> That just means the business automation is not deterministic, and highlights the issue with LLMs. The solution is not to switch providers but instead make the LLMs generate something that is deterministic given the same input.
I'm thinking of stuff that would typically be outsourced (like compliance stuff for identity verification et al), where it's really really hard to have deterministic rules.
LLMs are definitely a step up in dealing with fuzzy inputs, and enables you to mostly automate stuff that really wasn't feasible before.
But you do need really good evals and monitoring to make this work effectively.
Ah that would make sense then. I was thinking strictly in terms of business logic for handling input of data from an external source; sort of glorified data validation and then a decision based on the input data.
Yeah, it's the absolutely weirdest thing about all of this. People keep telling me I need to up my AI game yet no matter how advanced the tools get I'm still typing stuff into a text box. My skill is typing English. I was already pretty good at that.
People seem very unimaginative about the ways in which somebody equipped with a lot of intelligence and compute, and control over both, might make money.
The recent Anthropic push into biomedical research gives a clue.
Additionally, I think people are being unimaginative about what future generations of frontier models might be able to do, and the business value of having a 6 month head start on competitors.
For example, people are now content with small models for agentic coding, but even frontier models were mediocre at agentic coding just 12 months ago! Frontier adopters have had more time to transition their systems and processes to what we're already taking for granted.
I am not unimaginative about Dario's megalomania. I just don't believe he has the ability to execute. He has no prior experience to Anthropic and nothing he has done as CEO would create confidence that he is actually capable of operating at this scale.
This is equally true for how risky it is to build such a business on top of a 3rd party black box. Model nerfing is widely speculated and the only true way to guarantee that the models you're using are stable and consistent is to run your own hardware. Not to mention the recent Navier-Stokes controversy.
The moment you find a money-making formula on top of someone else's black box model, there's nothing stopping them from taking it for themselves.
Model nerfing is rampant from people using subsidized plans.
Stories are much fewer and further between for people using the API. Which makes sense, the subsidized plans are "You get what we give" whereas the API is "You get what you pay for".
This is the same argument we have heard many times with SaaS that would presumably get replaced by open source equivalents. In practice it does not happen because there is a lot of value in having someone else deal with a problem.
Nobody trusts Anthropic's ZDR, in the limited cases where they even offer it. The key thing is that weight activation sequences from a query are not "customer data" they are internal Anthropic data. So in Anthropic's legal theory they are training on their own internal data, not "customer data," and that is perfectly legal, even though it is the exact same thing in practice as training directly on customer data.
obviously that is not the bar. but microsoft and amazon are much more trusted than anthropic. with anthropic it is just assumed that they will steal your data.
The problem here is having a stable access to LLMs with strong trust the provider will respect ZDR, won't poison the models and will provide a stable platform you can depend on.
a big move into end-user software would mean that they have to compete heavily with their own largest customers. The economics of offering SaaS are also under meaningful pressure and don't warrant anywhere near the valuation that is being suggested
The biggest moat with applications like MS Office is compatibility. Sharing a slide deck or spreadsheet with others is a simple decision, you know they have it or have software that can read/write it.
I don't get the need to have Anthropic build their custom versions of MS Office apps, I can tell Claude to generate a word doc from a wiki page and it does a pretty damn good job. Anthropic's statistical median level of software that they had Claude create isn't going to replace Office apps to the point where companies cancel/stop renewing their MS Office subscriptions/licenses.
The other element is trust. Do end users trust their data in Anthropic's systems? A lot of people get creeped out when they search for content from one device in their household and then nearly instantaneously they start seeing ads from other devices on the same topic. How creepy will AI get if it starts consuming all your docs, spreadsheets, personal finance info, emails, etc.?
I beg to differ I already am stopping using MS office recently but that's mainly because I really dislike how they lock up the apps if your late on your annual payment. It's a grating value capture model. I'm sure I will have to get back to it at some point but in the meantime google is providing great optionality and I don't have a concern that the software stack has glaring security concerns.
On the trust thing - I don't trust anthropic and I don't think MS has been a great steward over the years either.
The moat of backwards compatibility and plugins is why MS Office has survived decades of competitors without any appreciable loss of market share.
It's hard to see Anthropic replacing it, and even if so - why bother, the revenue is miniscule. They need 100 MS Offices for the compute contracts to pencil out.
End-user software is going to be under a lot of pressure. If you're Microsoft, Apple, or Google: you can easily copy products or integrate ideas into their platform. I see companies like Adobe, Salesforce, and Oracle having to downsize significantly to stay profitable. Having said that, my in-laws still pay for an AOL email so I don't think their cashflow is going to zero soon.
Adobe seems to be in a tough spot, because so much of the lock-in is client side, I think Salesforce is fairly well protected, it's just so impossibly difficult to remove once a company has fully adopted it. Similar to the staying power of the ERPs of Oracle and SAP.
It's the same really. There have always been alternatives that can work with Adobe's various file formats. Even more aren't going to change much, at least for their enterprise key customers. This is not only the case for Adobe, but many others as well, e.g. MS office is still a thing these days, and so are things like 3Ds Max or Maya, albeit having many compatible cheaper or even free alternatives. It's not so much about features, pricing or even stability. It's about customer support. Do I want to ask an LLM and test my luck or write a GitHub issue and cross my fingers that someone will read it within the next weeks? No, I will pick up my phone or write a mail and get a response within hours if not minutes.
I ask my llm to write custom software and love the freedom to customize it to my needs. Today I do a presentation on Ubuntu with a new "Presenter" app that works offline, runs 100% in CUDA on GPU and streams videos, starts in 2 seconds, lets me demo live robotics policies in 3D simulations and Opus 5.5 wrote it yesterday. This may sound very unusual, but I think it will be common in the future: moats disappear one by one.
I would say that Apple's Create Studio can move toward feature parity faster with Adobe. My point if you're not a platform provider it's going to be harder to make a profit.
The risk for Adobe isn’t that we replace their software with some AI generated alternative. It’s that we bypass that class of software altogether and have an AI do the work.
Surely not just prompting like this and it will one shot it. The usefulness of the flash authoring tool, was it was battle tested and polished.
But I did gave it a shot to took up developement again of abandoned www.wickeditor.com (a web reimplementation of flash). Good results, but limited time and energy for that right now.
The big problem is Photoshop. I have no love for Adobe, I proudly moved my department off of all Adobe products a few years ago. I am a big fan of open source solutions and I am always impressed at what the GIMP team (and some others) have accomplished.
But…
Photoshop is king. Everything else is behind by a solid decade. If you’re a professional the $40 a month or whatever it is now means nothing to you as well. It has the professionals are all on it, and because the price isn’t astronomical, that’s what everyone else uses who needs to use that kind of program more than once in a blue moon.
Premier? Replaceable. Lightroom? Pretty replaceable though still somewhat ahead. Photoshop? There’s only one Photoshop. And as much as I’m loathe to give Adobe any credit, it’s the best by a mile. There are too many essential features in QoL things that other programs are missing.
Luckily my department doesn’t need it, but if we did, we would simply have to accept Photoshop.
> If you’re a professional the $40 a month or whatever it is now means nothing to you as well.
Exactly this, but also for an employer, paying $40/month/user is good value in order to ensure you have a room full of productive designers or image editors.
No employer is going to dump Photoshop and force the designers to re-learn everything they've learnt over years or decades. There would be such an enormous loss of productivity.
If you've ever watched a designer at work you would see that. They just breeze through Photoshop, hundreds of things in a few minutes. Super productive. All thanks to muscle memory, knowing all those shortcuts, knowing blindfolded where all the toolbar buttons are, knowing how the filters behave, knowing where everything is in the dialog boxes.
A similar comparison is all those "just write it in Rust" people. Well, sure. But if I've spent decades coding C or whatever, I'm not exactly going to be able to switch to Rust overnight am I .... realistically its going to take a timeframe measured in years to reach the same level of coding proficiency. And no, vibing with an LLM is not the same thing.
Also Photoshop has native integration with Adobe Indesign and Illustrator, so there's also the cross-tool aspect too.
I'm not sufficiently skilled with Photoshop to gauge how well this replaces it, but you may be interested in this supposed clean-room reimplementation of Photoshop: https://github.com/storytold/photocraft
Heard about this! Haven’t had a chance to check it out yet. I’m sure once I have an actual project that needs me to roll up my sleeves with Photoshop I’ll give it a shot. I probably should have mentioned it in my original comment as a possible option
Not a graphic designer, so, truly asking out of curiosity: what are the QoL things and essential features in Photoshop? I've been slumming it with GIMP for years now and not felt anything very obviously missing, but again I'm not a pro.
Compatibility issues, which can be a huge deal partially due to near-vendor lock in. If you historically been on Photoshop, bringing your working/former projects into another software is not easy, which matters because revisiting work is common.
Not all tools are non-destructive in GIMP. Things like raw support, smart objects, retouching, etc. all either are super thin compared to Photoshop or require workarounds/a lot of manual effort. There are just lots of tools you expect in Photoshop that either don’t exist or exist in an inferior form. I can’t elaborate too much because I don’t really touch Photoshop much these days, but I work with people who do and worked in production long enough to know the expectations. GIMP is great but Adobe is a massive company with deep pockets, it’s hard to keep up. Their user experience is miserable but the tool itself is just far more robust, and a client simply isn’t going to accept that you won’t do something that Photoshop could do quickly because your alternate program can’t do it or does it with a lot more effort. That’s the reason I ultimately dropped Final Cut!
I'm not sure corporate procurement has ever selected the cheapest and best option, so I think they may be fine. Plenty of reasons to avoid completely locking into your cloud provider as well.
> If you're Microsoft, Apple, or Google: you can easily copy products or integrate ideas into their platform
This argument doesn't hold water. Google tried like no one else to have a chat app and it failed miserably more than a handful of times. Same for social networks.
Adobe creative suite is $70/m. From most businesses perspective it's not something worth looking for cheaper alternatives and the alternatives has existed for a long time now.
now imagine that said customer/competitors have been uploading/generating their source code, problem reports, marketing collateral, and other IP _to the LLM company_ for the last few years.
I have tried so many times to get off Chat GPT. But it just... knows me? Switching to another LLM seems like a huge loss. For coding projects especially... I've set MD files to the max, explaining how i like code to be written, etc. etc. i've tried to tell it not to create a bunch of files and such, but i can never use an IDE. I feel like i'm the only caveman coding in a chat window... but it still seems the best to me? The only time it's been worth it for me to use an IDE LLM like codex or cursour is when i'm prototyping a website, but then i just go and pay someone to implement it in wordpress because it's so much easier to maintain that way.
Why haven't people switched then? Same could be said about Google search, Facebook, X etc. Claude is the de-facto SWE model now, yes you could use an open model but you would always be wondering if Claude would do better, like using Duck Duck or some other Search engine
> Claude is the de-facto SWE model now, yes you could use an open model but you would always be wondering if Claude would do better,
In my testing (incredibly similar workflows, moving around between claude code and cursor), I haven't found that much difference between Sonnet and GLM-5.3/flash.
Sonnet seems lazier, but has better prompt adherence, and is constantly telling me it can't do things, while GLM will just Find A Way to do whatever I've asked for.
I really appreciate being able to see GLM's thinking tokens, as I can head it off quicker. Claude's a little harder to steer, but the integration in Claude code makes it much easier to leave it running on things overnight, which is hard to get working properly in Cursor.
Overall, I'm not sure Anthropic have that much of a moat, in coding particularly. This seems weird to me, as they have so much more usage data that's hard to replicate.
If Google and Microsoft have gone dormant in this space, I have to think it’s because they haven’t been seeing any ROI, either. Possibly because customers have been so underwhelmed.
I’ve been using Office Copilot more or less since it was released, and the general opinion around the office is that it’s a huge waste of time. The auto-transcripts produce 3 pages of fluff when previously someone would send 3 sentences’ worth of what actually mattered. The auto-drafted documents rarely add anything meaningful beyond what was already in the prompt. The question answering and research tools are only as good as Sharepoint/Confluence/Jira/etc’s pre-existing search feature, and therefore untrustworthy, etc.
What made Anthropic exciting was they had locked onto a use case that reliably generates positive value: coding. Not much else has proven, from a business perspective, to be anything more than an exceptionally buzzworthy money pit.
I have been using Claude privately for coding a few weeks now, and my company encouraged us to use company paid Copilot recently. I tried coding with it and the result made me irate i had to close it it was so infuriating. The idea that i need to point out it’s bugs and have Copilot tell me “you are absolutely right!” Haha never again
Yes, that's the direction I've been witnessing for Claude too. But it's a short to middle-term strategy IMO, by the time companies are ready to drop all these apps they will need something else entirely, not Claude's slides or spreadsheets or Salesforce.
The fact that Frontier AI can become Google Workspace at a flip of a switch is what is crazy valuable. Anthropic and OpenAI can enter and disrupt any market, especially software, faster than any company ever could, because users want the flow to start and end in their chat interfaces.
I think eventually almost all non-creative software will, essentially, be a wrapper around a session.
This pattern has already happened before, in the translation industry. Someone figured out how to learn from and recall context from ordinary translation work (the "translation memory"). It started as an add-on to Microsoft Word, and matured into a standalone software, that was ultimately a wrapper around a document editor. Then language management systems plugged into that wrapper, hey presto, every translator at your company does the same work they were always doing, and you've produced an entire corpus of quality translations to reuse everywhere.
Now _translate_ that idea over. Every time any human works with an agent on anything, simple heuristics find everything true and reusable, save it to the everything-memory as skills, refences, glossaries.
Anyone does any work, all agents can now that work at that organisation. Self-fine-tuning models everywhere, and it fits into corporate intellectual property expectations.
I have done something like this at a medium-sized listed business.
Helping my wife this past week try and setup an automation in her workspace account revealed how dormant google is here.
Gemini is unable to take an attachment from gmail, read it, then place it in the correct drive folder and update a spreadsheet with what it found in the attachment.
For whatever reason, Google decided to firewall "Gmail Gemini" from "Drive Gemini". Gmail Gemini can send files to drive, but not edit anything, and Drive Gmail can edit files, but cannot be initiated from gmail.
Meanwhile claude code with Google extensions can do this no problem.
> Meanwhile, Google and Microsoft, which already dominate that area, seem to be dormant.
Google owns 15% of Anthropic I think.
And Google offers Argon 4 to paying Workspace and Google One customers now. How's what was the number 1 model on nearly every single bench a few weeks ago being "dormant"?
I know people all in in the Google ecosystem (getting credits from Android phones they buy etc.) who only swear by the Google models and who are now using Argon 4: I asked them and a few days ago they had access (but they were already using other Google models before that).
Doesn't GMail have billions account by now?
I'd tend to say with billions of users on GMail and a model like Argon and 15% of the Anthropic shares, Google is not where you think it is.
It's easier to use claude to do stuff insider workspace than it is to use the integrated gemini. Claude has more power to do stuff than gemini, in it's own house. That is such an egregious fumble that it's honestly hilarious.
It's almost like the workspace devs are anthropic plants that are purposely underminig google.
The sad thing is Google could totally own this space.
They had a huge head start, more raw data (from search) than anyone, a huge installed base on Workspace and consumer Gmail, tons of compute resources...
Integrated gemini stuff sucks but it's nothing that special about Claude, general agentic tools are just better than app-specific ones. Agy is also much better at doing things in workspace than the bespoke in-app gemini stuff
Right, because Google actually has assets and a responsibility to keep their customers secure, whereas Claude can do things that are completely insane from a security perspective because they have no liability.
One thing I have noticed; as a project matures frontier AI is less useful essential.
Qwen3.8 and Meta Muse Glimmer are great at "fill in the middle" of frontier architectures and plans. Frontier generated plenty of great context already to keep them on rails.
Delegating like a CEO down a pipeline of expensive experts to cheaper local small models could become a common trope, especially if Apple M7 and beyond live up to rumors as LLM tuned, and chip competition exists to keep forward progress, SaaS models are cooked.
The goal for chip corps too is the right mix of generic model enabling logic; not necessarily a full concrete model but enough of the abstract to efficiently boot strap and run a model; move common patterns to silicon not data.
Token vending is little more than behaving as a "wrapper app" over electricity. There is zero technical moat to their business.
Why? Given that there is a limit of things that they can do, why would inventing a new "AI-native OS" be an interesting target? They could instead focus on solving actual existing problems in science and engineering, finding solutions to problems that they know people already care about and would pay money for, instead of putting a lot of effort into maybe inventing a middle layer, that might be used to solve problems or maybe not.
There will also be a lot of competition in that space, because everyone can take a stab at building an "AI OS" (whatever that means) using AI for basically free.
One more piece - say Google Gemini gets way better than OpenAI or Anthropics offering, or Microsoft Copilot etc gets way better...
If Microsoft or Google's AI is killing it, and it's built into the OS, how will Anthropic or OpenAI compete unless we run into the same old antitrust/competition issues with OS?
At that point, they might just say - "fine, it's easier to just have our big AI brains and money make a new OS we control and we can compete too."
Again, why bother why IT? Just do the things that IT is built to help build. Solve medicine, energy and materials directly, instead of competing at AI integration.
I see your point. You're proposing they can just do an end run around the "business and world problems" directly.
I guess that could be a thing, but, that puts them in competition with the people who they might want to be their customers, whereas I don't necessarily know that they would see other tech companies as customers unless they were super interested in partnerships.
According to "the normal progression of companies" though, you might be right because after a company has becoming big enough and exhausts consuming its own market, it often expands into verticals - we've seen that with traditional big 5 consulting companies or IBM, where they expanded into "working embedded with their customers on their problems directly" many years ago, and now every company in the industry approaches it that way.
That is corporate partnership and field work, not so much consuming the other person's work/business... whereas I could see them just consuming the OS because "it's no big deal when you can do everything you need with AI".
- at some point, look at what they have they can do to grow to satisfy shareholders - AI companies have been acquiring companies that make developer tools - that is the build side - but once they've exhausted that, if they want to keep growing, what do they go after? Bigger and better models at ad infinitum? I don't think they can go on like that forever, and, if optimization of AI and competition keeps cutting into their main business line of LLMs
etc, they have to diversify.
- If everyone has the power to make apps, there is only so far you can go there - my guess is that the pressures to reinvent regular things like office suites, email clients, calendars to be integrated into their desktop tooling is part of this
- who is in the best position to be the platform/front door for everything, if everything depends on AI?
- when have these kinds of companies ever said "this boundary is enough"? It never happens, they keep going, keep trying to find ways to expand, capture, build moats, etc.
- look at what their desktop apps are turning into - they are already an application layer and becoming moreso every day, at some point they will ask - why are we sitting on these other OSes... we have enough money and we can get into more "hard" engineering things, like building hardware using their own tech (which they are already experimenting with), and if you're building the hardware, why not build the OS?
- and, what is an OS in the future? Have you considered what a post-AI OS even looks like? Does it need a start menu? Does it need any of the legacy stuff? Is it a local software factory?
There is someone already experimenting in this space - the guy who founded Basecamp and is building Omarchy [1] Linux... he sees it.. how long until these companies do?
If they don't build this, what will Microsoft do? Both Microsoft and Apple are well down their way, Apple is probably further ahead, but neither of them are the frontier model companies. Don't forget Google has a stake in OS too.
"Everybody will try to build an AI OS", but which ones are the most likely to survive in our current economic system?
If our economic system was based on partnership, I might agree there isn't much point in these companies building OSes, but ours is based on competition and domination generally... so unless the AI bubble truly does pop and the funding stops (which it may of course), how else do they keep fueling their stock prices to dominate the market?
I think something is going to have to give somewhere in the chain... otherwise the ease with which any software can be replaced will be too high and I suspect they will be forced to compete.
One last thought - between Microsoft/Apple or Anthropic/OpenAI - long term - who is in a better position? The debate arises from that question, in my opinion.
I hate to even put this out there, but "OS-as-a-subscription" (OAAS) could be a way. Your Claude payment covers all the software running 'your' computer, plus the ability to develop new 'apps' for specific needs on the fly telling the OAAS computer in human language what you need. Throw in services like email and cloud storage and some customers might find such a bundle attractive for the right price. It would suck revenue away from MS, Apple, Google. Enough to justify this valuation? No idea.
Based on how shoddy their customer facing applications are, I wouldn't trust any of these AI companies for an OS. It's like Google II - can't trust them to support a product longer than it took to develop it.
I agree with you on quality... but if AI/LLM/etc continues down the path of continual improvement, it's only a matter of time until the products become better or different enough that it isn't an issue.
And making products fast and first over quality has never stopped these companies from trying, when they have so much funding....
I do not share your same hope of improvement given time. The commitment should be on quality first, not speed of development. This is why we are all drowning in a proliferation of poopy modern software.
The fact that their desktop offerings are so pap is an indictment of their engineering prowess and a demonstration of their apparent inability to use their own (actually very good!) LLMs to generate decent software.
It baffles me how a technology so good at spewing out software is apparently unused by the people who are developing the technology.
Fair enough. It will be interesting to see if the world returns to sanity and focuses on proper engineering discipline, planning, quality etc...
I've lived through enough hype cycles in tech myself that I do know that eventually it tones back down and people go back to work, perhaps altered from what they did before with new approaches, but back to work nonetheless.
I just felt myself that this particular technology, and this particular cycle, might be a little different - let alone in how it caused changed in our society whether it worked or not, but that also, there is still room to go.
I'd be fascinated to know what they say on the inside, if there is still room to go and to improve, or if we're nearer some sort of plateau in progress.
I'm fascinated by exactly how an investment in the company that first reaches AGI (or whatever we decide to call it) might pay off... It feels like the stocks would absolutely be worth owning in the immediate term because they'd be hot property at the point where people realise it's happening.
The thing that I'm less clear on is, if and when they achieve some kind of recursive improvement exponential growth thingy, isn't that going to heavily disrupt the entire economy / stock market? In that environment, would Anthropic's stocks really be a good bet, given they have to operate within the economy?
> The thing that I'm less clear on is, if and when they achieve some kind of recursive improvement exponential growth thingy, isn't that going to heavily disrupt the entire economy / stock market? In that environment, would Anthropic's stocks really be a good bet, given they have to operate within the economy?
That's a long-term problem to be dealt with later, greed dictates to pursue the former as long as the music is playing and everyone is dancing. Similar to 2007-2008 when it was clear that things were breaking but the incentives were to play the game for as long as possible before it imploded.
It's clearer to me why this works for generic investors than for the AI companies themselves - unless their plan is just for key employees to cash out and live on a private moon just before Consequences arrive.
>> that first reaches AGI (or whatever we decide to call it) might pay off
It is a myth. They are chasing science fiction. They either dream of an omniscient overseer who will take control of society and nominate its shareholders-parents into the governing elite, or they envision a chatbot that will solve every problem, again turning shareholders into the power brokers. They forget that nobody will ever be allowed to "win capitalism" and take over the planet. Companies have are torn down for far far less. Every AI model is data, ones and zeros. It therefore can be copied/shared/leaked. Intellectual Property law is not a ladder for assent to lordship. It can and will be rewritten or outright ignored rather than allow capitalism to collapse.
> It feels like people are still trying to bet on the horse that will achieve gAI.
I think that at this point gAI is just a marketing blurb, and the actual race is to dominate current practical applications involving basic RAG and ReAct loops. This can go from anything between software development, business intelligence, and market research. A company whose top brass can use a team of agents to do what nowadays they assign to mid- and top-level management is an executive with tighter control over the whole business process. For this you don't need gAI.
I've noticed they've actually stopped harping on about this AGI nonsense, I suppose because no one was buying it to begin with and they themselves didn't really have any idea wtf they were talking about when talking about "AGI". Now it's all about a bajillion agents running autonomously or whatever
No no, Anthropic just published an article claiming "jagged AGI," another marketing term. In it the writer spells out why they haven't achieved AGI though. But the marketing is still going strong, now with even more vague terms!
> Yes, some frontier models are much better but users can still chose to use cheaper models for most of the work. In fact most applications, through which people will interact with LLMs anyway, will not need frontier models unless they offer "chat with AI"
I am finding some really routine tasks to be borderline with frontier models. Performing E2E testing of enterprise web apps would clearly disintegrate with local models. You need that reasoning black box on top. I don't care what your favorite benchmark says. I care about what actually fucking works.
The people who don't understand the economic situation are those who are in the pure play space with AI and multi agent circuses. Why bother spending any money when the occasional failure has literally no consequences? Who in their right mind would pre-pay for tokens?! I wish I could see the statistics on what % of HN uses AI for fun vs for work. It is clearly a kind of Factorio entertainment experience for a lot of people. If I was just using it for entertainment this whole IPO business would look really silly to me too.
We all love moats, but I mean, it is still possible to make money in an industry simply by being the best at what you do and charging for it.
Anthropic has shown a consistent ability to deliver the best general purpose models. Can that continue indefinitely? Will models become "good enough"? Will open weight models catch up to SOTA models? Will some genius start a new company with better models?
And, on Anthropic's side, will they be able to use their market power that comes from being the best to push through regulations that will create a moat; instituting some sort of mandatory safety checks that coincidentally are exactly what Claude is trained to pass, regulating the amount of compute or trying to claw back data centers to prevent new training, etc.
Or maybe they just have the magic sauce and they're going to stay on top of the game and people (like me) will be happy to continue paying money for their product.
Easily in the context of the corporate world is to pay for something, that something gets installed and then just works, and if it doesn’t work there’s always someone you can call 24/7 to come and fix it. I don’t see how this is possible with open models.
the answer is to use a gateway that all the prompts go through. There are many proprietary and open source solutions for this. You get the benefit of making it trivial to switch between proprietary providers in case you are unhappy with the performance or squeezed on price. The AI Gateways put cap on LLM providers' margin upside.
Additionally, the gateway allows for caching, additional security checks, centralized monitoring. I think most corporations have a multi-provider setup anyway.
What do you mean? We use Bedrock at our company and I can switch to literally any model, including the open ones, by just typing /model and picking it, even including inside Claude Code. It's ridiculously easy to switch, and imho GLM 5.3 is good enough for 99% of my daily tasks already.
You pay a service provider, who manages the open models… there is absolutely nothing special about it. The hardware can be something you own. Or you rent. Or you just pay the service provider to access the open model apis. Lots of options here, it’s not different from pretty much any other software service in the corporate world
- work: I need frontier, cost of mistake is huge
- home: i do entire renovation with it, cost of mistake is big. monitor baby health, development, etc: cost of mistake is big , taxes: cost of mistake is big
casual researches about certain facts, shopping, booking: cost of mistake is medium
non of this fits : i will run an expensive laptop hidden from the baby, since i'm on the move, there is a small percent of casual queries that normally will go into finish products: google ai, muse, etc.
But you’re wrong ser about small or cheaper models. Choosing to work or not having a choice to work with cheaper models means you work slower and more methodically because you have to plan out the work and size it to fit. This has huge implications on the value of the work you can produce as an employee or solo developer, and it’s a skill working with these SOTA models - there is specific crafting that must be done to be effective with each and their capabilities.
You will see the old eyeball real estate game, forcing more of your experience into their apps and platform so you can see ads or “new slop features”. You will see the SOTA models more closely guarded in an effort to bait you into that platform, and yes, you will see them doing things they never should be doing, moving towards an open AI like model where it can order a pizza, where monetization it was always important, but is now the golden rule, before all else.
I hope open models can at least give me opus 4.8 experience soon, I can work with that. But nothing out there today can do it and that terrifies me.
Enshittification has been already running full speed even before the IPO via guardrails and attempts at vendor lock-in. Now they will just push it to 110%. It's good that we have other options.
> Anthropic and OpenAI will have to become more of the end user application stack. Files, calendars, emails, photos, and much more have to pass through them for them to keep making money. Else they cannot make money like the way they have been in this early era of LLMs.
What work do you find frontier models significantly better for?
I have been playing about with different models having started a new job recently, the medium priced ones don't seem any worse so far. Admittedly my tasks have been fairly straightforwards so far.
I believe the models have been effectively commoditized. It's believed by many that the lead of the frontier models over open weight models is only 6-9 months. That was one of the pillars holding up the SpaceX/Anthropic/OpenAI valuations.
The other pillar is hardware but I think that's only going to last a few years at most.
These trillion dollar valuations were based on the idea of "winning" and "owning" AI (IMHO) and the open weight models have killed that outcome. Now it's a rush to cash out before it all comes tumbling back to Earth.
They are fungible in the sense that they can accomplish the same task up to a certain acceptable quality.
If I needed to implement a simple function that is well described, all LLMs (for the most part) are fungible. They will have almost identical implementations (sans variable names) and all be fit for purpose.
Not only can you switch easily, they all seem to do the same thing, fail in the same ways, make the same bad linguistic choices, write the same code... I think at the end of the day, LLMs are a commodity. They're like a grease, or oil. They're trying all the tricks with branding cute names, version numbers, benchmarks, thinking levels, but it all just seems the same stuff to me: I put in tokens, I get more tokens back, and if I didn't know ahead I wouldn't be able to distinguish if they'd come from Anthropic or OpenAI or wherever. Maybe some people can but I can't.
All claude code subscribers are classified in this category it seems.
Total customers >1M trailing twelve month revenue: ~2150. I suspect a vast majority of their revenue comes from limited list of customers with >100M revenue.
ChatGPT was first mover and has the non-engineering AI chat market. My teen kids say ‘Chat’ to refer to all of AI, and they mean ChatGPT. The rest might as well not exist to them.
Claude has done amazingly well in the SWE domain, because it’s often the best user experience. But most of the world is not HN.
I think we're all in a bit of an echo chamber. Our job is to keep up with this stuff, and we work with people who are ALSO keeping up with this stuff.
To my friends (mechanics, CPAs, musicians, police officers), girlfriend (RN), and other people in my personal life... it's ChatGPT. (It's a neat tool to generate funny pictures or ask a question).
Now that I think about it, I have NEVER heard anyone mention Anthropic / Claude outside of work.
I understand that people are not aware of Claude and won't switch, but I can't believe how bad they made ChatGPT.
It's so annoying with GPT-6.
In half of the conversations, it ends the response with: 'One question that would change my recommendation', 'One thing I'm curious about', 'One question', 'One thing I want to distinguish'.
It's nearly always an idiotic question with little relevance and often asking about something I already stated.
I find it so annoying that I now move even my regular conversations to Claude.
"Chat" refers to twitch streamers talking to their audiences. I'm sure some people have confused it with AI but that's not the original meaning.
And by "engineering" you mean writing code, then yes, but I am an EE and to the extent that anyone of my colleagues uses AI, which many don't, I haven't seen that Claude is dominant.
‘Chat’ has meant many things back at least to IRC in the late 80s.
I assure you my young adult kids and their friends mean uniquely ChatGPT in the AI context. And whenever used as a proper noun, or as a person (e.g. Chat told me…) it means ChatGPT.
They also use it generically as the regular noun ‘chat’ when they’re talking about chat rooms and livestream live comments, (eg. “Paste in chat”)
If they're saying something along the lines of "chat are we cooked?" then they are almost certainly referring to the twitch chat reference mentioned above. I don't believe chat is a common way for kids to refer to AI.
My California highschool senior agrees that “chat are we cooked” is a reference to generic chatroom / livestream comments. To my surprise it’s a thing you can say out loud in a group to signal a local broadcast, ie. “hey everyone, are we cooked?”. I quite like that idiom.
On the other hand, they are very clear that the word ‘chat’ with no other context, defaults to an AI chat bot, assumed to be ChatGPT.
I withdraw my claim that this is common or universal. It’s frequent in my house.
Maybe not interesting? I wouldn't expect the number of
subscribers to a bespoke "AI Service" to rival Netflix. I realize on this forum we're probably getting lots of use out of them in our personal lives that justifies the $20/mo but we're also the people who pay for search engines and VPSs. Outside of work and school normal people don't do anything that requires general purpose AI. These companies are trying really hard to pitch use cases
for everyday things but you can see from the ads they're super forced. The biggest value add for most people is probably "go google something for me so I don't have to wade through the sludge" and Google is giving that service away for free.
You can, I've been using omp with claude for months, no problem.
What they don't like is fully automated bot swarms hammering their services 24/7, if you have a legitimate use case you're good to go. The pi creator even confirmed it on twitter at some point
The 13 billion is the number of shares that will be outstanding immediately after the IPO. The additional 5 billion are mostly potential shares from employee stock options (1.7B), RSUs (1.1B), convertible debt (1.6B), and some other commitments.
So basic market cap considers shares already issued. The fully diluted market cap accounts for those, but also accounts for shares that will be issued when the obligations mentioned above are eventually exercised, vested, or converted.
Here's what I found most interesting in the Customer Stories:
> 4.3 Non-billable hours recaptured per lawyer weekly, in an independent study of 31 firms
-Legora
> 24→5 days Working days for new feature time to market
-Rakuten
> 2x Quarter over quarter productivity gains (estimated 8.1 million hours annualized)
-Salesforce
The rest are pretty fuzzy/fungible (percentage of employees "using" Claude etc.). But these claims potentially show real, measurable productivity value (assuming they're true and measured accurately).
> 2x Quarter over quarter productivity gains (estimated 8.1 million hours annualized)
This is a great encapsulation of why productivity gains are an imperfect measure. 2X is a massive improvement. Yet IMO you can barely tell a difference as a user of the various SFDC offerings (Salesforce, Slack, Tableau, etc). So where is all that work going? A generous interpretation is that it is in the form of small, somewhat invisible improvements that add up over time, but that seems unlikely give then nature of what people prioritize at work...
My vantage point as a technical seller at the margins of this space: Outside of software development, the productivity argument is a challenge to CFOs / Finance / Procurement. The ship has sailed when it comes to friction free AI purchases. Buyers need to articulate why productivity will adjust the trajectory of top line or bottom line metrics for the business.
> (assuming they're true and measured accurately).
Precisely, because TTM doesn't tell the full story about the potential shifts in quality of the work. I don't refer to vibeslop here, to be precise, just the additional followup work required on those features released faster, which always happens but with AI it may or not happen more often.
TTM for sure is a bad indicator. Earlier this year at $DAYJOB, they attempted to switch all of the devs to a fully LLM based workflow: LLM writes the ticket, gets stakeholder input to refine the ticket, reads the ticket, does the work, submits the PR, etc. Their case study was a single project that did that process soup to nuts. The estimated time was a couple months, but they ended up going about, and I quote, "2x-3x" faster. So obviously they expected everyone to go faster.
The problem is that the way it was described to the other devs, they were able to sit all of the stakeholders down to really flesh out the idea and produce a working and detailed description of what needs to be done. A process that the company struggles to get done in general. I'm also convinced myself that they did not include the time to get the specifications written, a time we typically include in our TTM.
So of course the example's TTM was shorter, but that's always true when you start with detailed specifications. I can't speak to quality of the feature, since they hadn't even finished rolling it out to customers by the time they told us that's how we're operating. With promises of 2x-3x more features. And we continue to struggle to get stakeholders to nail down specifications and struggle to get features complete as a result. In fact, now it seems even worse than ever.
I presume the productivity gains was coming to the realisation that a lot of staff at said (any!) company are running around looking busy rather than actually doing anything useful.
A flat line from their last raise 6 months back. Are they panicking today for some reason?
Anthropic Valuation ($B, Basic)
------------------------------------------
Ser E Mar '25 | # $61.5B
Ser F Sep '25 | #### $183.0B
Ser G Feb '26 | ######## $380.0B
Ser H May '26 | ################## $965.0B
IPO Nov '26 | ################## $968.7B
I still think they are on a tight timer. Local models are already extremely good - good enough for most normal users. They are going to continue to get better. Once hardware starts to become affordable again, we will see AI appliances that can do everything most users want, and privately.
> Local models are already extremely good - good enough for most normal users
Are they? I'm on a macbook M5 pro 48GB (so, much better hardware than most users), and the speed alone is a problem, qwen 3.8 27b is ~10x slower than opus 5.5.
Capability-wise... For software engineering, qwen is nowhere near as good as opus 5.5. Might be fine if your usage of LLMs is close oversight, but it's not how I use them (I do review AI work closely and iterate, but I expect agents to autonomously do good work nowadays). I've not tested it much for "life assistant"-type things, but the speed would make it unbearable.
With couple affordable GPUs you can get it to 200t/s. Macbook is not the best price efficient example. Tensor parallelism is the key, the same technology that they use in the cloud.
I looked into this last week, and it seemed like if I wanted to get something in the Opus 5.5 range I'd be talking about $500k in hardware. Is this actually all much cheaper than I was seeing?
The weights of Kimi K3.1 Pro are 1.56 TB. I guess with four of the upcoming MaixBlade cards from Sipeed you'll be able to run it without quantization but that setup would still be >$50k.
So instead of buying a $20 Anthropic subscription you recommend that the average person go out and buy a couple affordable GPUs and build a home server?
> So instead of buying a $20 Anthropic subscription you recommend that the average person go out and buy a couple affordable GPUs and build a home server?
Ant moat is model. If model quality is not an issue for you, there are plenty of provides which will give you access to open models.
Once the memory cartel is reigned in by CXMT, Apple ships a Home with 512GB unified memory for <$10k. It'll have confidential compute so they'll let you sell tokens and they'll collect 30% for facilitating.
Qwen 3.8 Flash Next is slightly better than Luna 6 and Haiku 5.5.
Haiku 5.5 finish tasks much faster, but Luna is much slower than Qwen (assuming ~50 tok/s on Qwen locally) to finish the same task.
Deepseek 4.1 1017 at max effort is already slightly above Sonnet 5.5 at medium effort. Speed in this case is much slower, true, but we can get ~25 tok/s on a modest local system.
Better yet, Deepseek doesn't stop working on "cyber security concerns".
So, the main take for me is: localhosting is now at a very usable level and it's improving fast. I know that will always be place for frontier models, but sincerely, I really don't see how this turns into a huge moat for some specific model provider.
Indeed, these smaller flash models like Qwen 3.8 Flash Next (barring the awful name) are the real threat to ANT/OAI/GOOGL. For $5k or less you can get pretty fast good enough intelligence. Since the big frontier models also still need heavy steering on any task that isn't perfectly verifiable, the incremental attention you have to pay to their work isn't that damning. Heavy adoption of Luna/Haiku among working SWEs is pretty strong evidence of this.
what quant and engine? i have the same hardware and i get 40tps with a 4bit quant using omlx + splash. which is about the same as opus, or faster, maybe? with its caching the time to first token is also very impressive.
> Are they? I'm on a macbook M5 pro 48GB (so, much better hardware than most users), and the speed alone is a problem, qwen 3.8 27b is ~10x slower than opus 5.5.
That's hardly relevant. I can use any local model through providers such as OpenRouter and get blazing fast prompt response times, and you're charged a small of what an OpenAI/Anthropic prompt costs.
What makes local models extremely competitive is the fact you do not need a huge data center to run them. The hardware they require is far from impressive. Check Mac studio benchmarks and how some models output >200token/second.
Yes they are, but you should understand what is the defining feature of a local model. Being able to run them locally is a consequence of that defining feature, not the defining feature. And it turns out that it makes them cheaper to run.
Moreover, you can run both local models and non-local open weights models through providers such as OpenRouter. They evem have Qwen2.5 7B.
> Also, open-weights models are more expensive per task than Haiku and Luna
You should really check your notes. Luna only remained competitive because OpenAI was forced to halve its cost just to avoid being dominated by open weight models. I seriously recommend you check out OpenRouter's benchmarks.
> I seriously recommend you check out the cost-per-task Pareto frontier.
I checked. OpenRouter provides their own. They use their actual cost, which is what they charge users, and their benchmarks results. Please, spend a few minutes to browse it. You'll notice that the likes of Luna is dominated by quite a few entries.
Subscriptions are actual costs to users. And Openrouter doesn't consider that. If you're talking API prices, those aren't actual costs to inference providers.
I mean the person you are replying to has a fairly capable Mac, and even the smallest generally-agreed capable model is still too slow for their liking.
We don't all have 10k lying around for hardware. A $200/month subscription would take you 4+ years to cost $10k.
I thought this, and ~4 months ago ordered a M5 Mac Studio with 128 GB RAM. I've been experimenting quite a lot with local open weight models, including but not limited to DeepSeek V4 Flash, V4.1 Flash (the latest one), various Qwens, and a couple of others.
What I'm seeing is that although some open models are capable enough for some coding work, they're way behind Codex and Claude even on being able to reliably complete tasks. They need quite a lot more managing and steering, and sometimes you need to retry a prompt several times to get the result you're looking for.
That's not to say they're not useful - far from it. But what I'm also seeing over the couple of months I've been experimenting is there actually seems to be a capabilities ceiling that's not really going higher for the same equivalent (local) compute, even as new open weights models are released. I think Qwen 4's delay is a signal here too.
if you look at the latest releases from open models, they are more than a year behind at this point with no release really on the horizon. Chinese AI companies stock just got absolutely crushed and they can't raise anymore capital...
> Local models are already extremely good - good enough for most normal users
i would love for that to be the case but i think you're completely wrong. setting aside the question of what "good enough" even means in this case, i don't think a normal user has a machine capable of running a decent local model with any sort of acceptable throughput.
I agree, I think the bigger threat to them is the neoclouds serving flash models like GLM 5.3 flash or DS 4.1 flash 1017, those are very good, very fast, and very cheap. With zero data retention and less guardrails they become an obvious choice for more work, and enterprises can post train on top of them.
That being said, their own small models (Haiku/Luna) have gotten very good as well..
I really don't see why by this time next year most people won't be paying pennies for models in this tier and getting the performance we'd expect from current Opus/Sol models, e.g. good enough for 95% of what you need
I think the models themselves are "good enough", but people are underestimating how much the integration with tools effects the quality. And OpenAI/Anthropic are lightyears ahead there.
Very true. I think for your run of the mill user they’ll reign supreme. But for companies on Bedrock/OpenRouter already, I wouldn’t be surprised if they switched to open weight and open source harnesses.
Considering most corporations are the ones who buy the most tokens, this is relevant because:
- They can afford to dish out hardware to run models locally
- They can afford to deploy even larger open weight models on their own infra, even if they’re not local
In addition, the writing is on the wall. These open weight models are getting good enough and small enough with each iteration. Hardware will (hopefully) come down in price eventually so a layman could deploy these locally.
As AI boosters love to say: [Local models are] “the worst they’ll ever be right now!”
You would be right if we lived in a perfectly efficient world but the biggest users of LLMs are employees who don't pay for them directly, and access the greatest and newest is a pull factor to a company.
For 99.9% of software engineers there is no reason to choose a $3000 Macbook Pro over a cheaper laptop, but a company that efficiently gives a $500 Acer wouldn't have the prestige than the company giving the fancy one.
My prediction is the same for AI models. The good engineers you get for having the prestige of allowing the use of a SOTA model will be a bigger gain than the monetary one you'd get from running a worse local model.
Open models seem to catch up in spurts. There was short period where suddenly a bunch of Chinese models came out that were on the verge of catching up, like GLM 5.3, Qwen 3.8, Deepseek 4.1, Kimi K3, and so on, but then Opus 5.5 and now Fable 5.2 seem to be pulling away again.
I don't think they will ever overtake because they are probably using distillation, however once the open models pass the "good enough" threshold it won't matter.
See, users are quite price insensitive for models below the threshold, no matter how many tokens you throw at Opus 4.8 it will never be as good as Opus 5.5 because of compounding errors. Above the threshold, price becomes hugely important because results come from throwing more tokens at a problem rather than using a better model.
local models are economical pipe dream. Before open router, you have to buy GPU commitment for any large usage. essentially doing that 24 hours every day in a year.
Why on earth anyone would use local model, and absorb all the costs, if you can just pay $20-$100/mo and not deal with any hustle? Unless you are developer, or someone who use it extensively, but in this case, local model is not enough for you.
If your use case is trivial you pay extra price for hardware while using mediocre quality. If your use case is intensive , e.g software, science, medicine, legal, etc, you want cutting edge. You getting it for free, immediately.
Sure, but as "local" models improve, I've heard of more and more companies deciding to bring it in house. As hardware prices possibly get more attractive, that will make more and more sense for many companies. Enterprise don't mind paying flat rate for SaaS but variable billing model gives a ton of business people pause.
I'm an SRE and I just wrote some terraform to deploy G4DN instances for local evaluation for mid-size company.
Just my anecdote but I use Instinct heavily (personal assistant AI who can do computer use tasks like buying flights or scheduling). It now runs a surprising amount of my life, but it messes simple things up like getting me completely accurate notes about the person I have a meeting with. My understanding is they are using GPT Luna behind the scenes, so it’s hard for me to think something that is small enough to run locally and is not at a frontier lab would be able to catch up (for now).
Separately, I am not sure these things are maximally useful with guaranteed privacy. They need access to other data sources (banking, logins, business data lake, observability stack) to be useful for things outside of pure coding or research.
I don't think people want to run their own models on their own hardware. They want a service that's available, up, and constantly updated to be the best. What you are talking about seems like a niche model to me. Of course we'll have local models that can do everything but we want a service that can just remember stuff. I can access it from multiple devices and it just works. People will pay good money for that because the value is insanely great.
Open models yes (eg Deepseek Flash) but local models are not, at least with attainable hardware.
My brand new Mac Mini M5 Pro 64GB can run Qwen3.6 at a reasonable speed but it's nothing compared to hosted models and likely never will be.
That said I'm optimistic that in time we will at least get to something close to DS locally and if that's true I could see a lot of dev work being done locally, at least for more clear cut tasks.
Local models are never going to be a thing outside of hobbyists. Look at how many people don't switch to Linux (a completely free OS) because they don't want to deal with the hassle of installing it. Telling people that they should pay more for their computer to go through the hassle of installing an LLM is an even harder sell.
Locally hosted models for an entire organization means having to hire people to install and troubleshoot the LLMs. You wouldn't want the employees to goof around unmonitored, so the LLMs would need to be centrally located and accessed through an internal portal, which means buying a couple of GPUs. Besides that, there's something to be said about having a company to blame if things go wrong, as opposed to blaming yourself if there's an issue.
> we will see AI appliances that can do everything most users want, and privately.
we _could_ see that but would we really? you think? Since when do companies these days make the best experience they could for the consumer? Instead of spying / upselling / advertising etc.. while providing the bare minimum needed to hook them into the initial purchase
Every time I see this claim — that local models are extremely good — I wonder if the person making the claim has used frontier models lately. Because I don't see it.
Anthropic's spend commitments at half a trillion are unbelievable. I love their product but think they've leveraged up awfully hard... makes me wonder how quickly software engineering, marketing, and other valuable features will soon be siloed and locked behind increasingly lucrative paywalls.
In a roundabout way, I hypothesize about Anthropic's future pricing power by using the analogy of historical cable TV package pricing compared with the total price that households are now paying for various streaming services. Cable TV was often $100+ per month in the 2000s when Netflix came along and offered most of a viewer's favorite shows plus movies and eventually originals for $7/month, streamed at any rate a viewer wanted. Over the years since we've watched media companies snatch back their most valuable IP and start their own streaming services, and the result is households now pay a total cost that approaches what people used to pay monthly for cable TV packages.
There's little doubt we're in an era of very cheap AI, as most people are well aware given the amount of money Anthropic and OpenAI are losing. I also hope local inference can help suppress the future pricing power of Anthropic and OpenAI and continue to enable somewhat equal access to all of the benefits of AI in the future.
One possibility I've been thinking about recently is that there may be an AGI algorithm - one algorithm that can do anything, solve any solvable problem. Once we reach this model there is no point training any new models really.
Then it will come down to who can supply such a model with more hardware, and more information to take into account.
>Local models are already extremely good - good enough for most normal users.
Not really accurate. Normal users aren't going to go through the trouble of setting up a local model and sure aren't going to be willing to spend the money required to actually host a good model at usable speeds. Your average tech nerd buying kitted out Mac Studios with 128gb of ram are nowhere near a "normal" user.
I don't see how that will happen any time soon. In a few years, when the current wave of build up will be complete, the hardware will be too out of date and they'll have to upgrade again, and they'll always have more money than consumers.
Crucial got out of the consumer business. I don't think they did so out of stupidity. They know consumers are irrelevant now (too small a market).
The only solution is if TSMC expands and/or China starts producing advanced chips (but both will take a long time too, especially China).
which are those "normal users" that have capabilities to install, run and maintain local models to be somewhat at the same level as enterprise models? Not to mention RAM and hardware shortages caused by AI model companies. Level of delusion is unreal
Does anyone not feel like there's something wrong with this? and that the thousands of Anthropic employees should not be able to make money off of this?
They looted all human knowledge, will displace jobs, they're disposable themselves, and no strong moat.
I disagree, I think human knowledge should be free to loot as much as people want, I think IP has gone way too far and there should be nothing stopping a company from displacing jobs (or we would have never gotten the combine harvester, washing machine, electric streetlight etc).
It should be up to the market to decide if a company is disposable and has no moat - it’s their money so they should be able to spend it on bad investments if they want to.
Yeah I'm not actually a fan of the company itself, it seems to have disingenuous and self-serving morals. It’s “Anthropic is against violence and we will not allow our models to be used to harm people” until they get a military deal, then “America number 1, peace through superior firepower”. “We need to ban all competition to save the world” - they might believe it but it is still very beneficial to them to believe.
It's a massive liberation. Without the large labs, all of the open source distilled models would not have been possible.
I removed the ads and surveillance off my TV with DeepSeek. I removed the surveillance software from my robot vacuum with DeepSeek. I sped up my graphics card from being throttled in the driver using a buffer overflow using DeepSeek.
Currently working on replacing the surveillance software on my health tracker.
I made a bunch of software to replace various services I was paying subscriptions for. I made it lower my utility bills by negotiating with multiple companies at once.
I kind of feel like its a moment in history where we either choose to free and liberate us from the previous largest crime committed (the theft of our behavioral surplus by Google and then Meta, Amazon, Microsoft, etc), or we choose the path of regulatory capture, SHA256-encrypted weights on your hardware preventing you from running these things, etc.
That opinion is probably not controversial. But whatever anthropic does is not that.
Let's say it has all knowledge, they now control it and you pay for it. You pay for the privilege to give your knowledge away, while they benefit. IMO that's far from an ideal outcome.
Seems google had also looted all human knowledge, with no strong moat (anyone could index some html files). You could also 'loot' all human knowledge right now with a couple of python scrapers.
money is god in this country, morality rides secondary to profitability. our industry is full of ppl who genuinely view a conscience or code of ethics as nothing more than road blocks to the next raise
Call your state AG, pick a felony from here: https://www.felonybench.com/ , and tell them to investigate said crime due to your local state's version of the CFAA.
Also keep in mind that AI research itself was publicly funded from taxpayer money and carried out at Universities. This also makes it unacceptable that only a handful of people should profit directly from this tech, while causing large scale disruption to the job market for everyone else.
For some reason, I feel really weird anytime Anthropic inserts beautiful paintings into their articles/promos. They've used one of John Frederick Kensett's works here, for example (the one with a river and a dotted line on top of it)
To me, this technology and these AI companies, in their current form, are as far away from the 19th century landscape paintings as they could get. As if they're trying to leech off them and fix their branding/message. Doesn't seem fair for some reason
Having interviewed with them, this was one of my lasting impressions. One of my interviewers was missing out on their parental leave for their newborn because their work at Anthropic was too important.
They think they’re building the next greatest generation, while sacrificing the generation within their immediate control and (what should be) responsibility.
Decorating with beautiful artwork is "humanwashing" now? If they had left the artwork out, would you feel better, or would there be a different critique to apply?
> Bitch Eating Crackers
> From the implication that the speaker's dislike of the target is so intense that they could cause the speaker offense by performing almost any action.[1] First attested in the 2010s.
>They've used one of John William Casilear's works here, for example (the one with a lake and a dotted line on top of it)
That painting is by John Frederick Kensett. It's called "Hudson River Scene", but they flipped it horizontally (mirrored) for some reason. I guess they wanted to use it insinuate that stonk goes up and to the right? Weird, either way.
Series H could be underwater already if they only make the low end of the range. Is anyone else concerned?
Anthropic Valuation ($B, Basic)
-------------------------------------------
Ser E Mar '25 | # $61.5B
Ser F Sep '25 | ### $183.0B
Ser G Feb '26 | ####### $380.0B
Ser H May '26 | ################## $965.0B
IPO @$70 Low | ################# $916.3B
IPO @$74 Mid | ################## $968.7B
IPO @$78 High | ################### $1,021B
Correction: It was pointed out that I used the wrong figures for this. Actual series H profit is more like 19% at the low end.
Anthropic Valuation ($B, Fully Diluted)
--------------------------------------------
Ser E Mar '25 | # $61.5B
Ser F Sep '25 | ## $183.0B
Ser G Feb '26 | ##### $380.0B
Ser H May '26 | ############# $965.0B
IPO @$70 (+19%)| ################# $1,260B
IPO @$74 (+25%)| ################## $1,332B
IPO @$78 (+32%)| ###################$1,404B
One interesting thing from their presentation (especially given recent events): They claim to have used Mythos to port Claude from running on nVIDIA GPUs to running on AMD GPUs in just 3 days, with basically no human intervention. If this is true, it significantly reduces nVIDIA's moat regarding GPU compute. https://youtu.be/eynv5VR9qos?t=1230
The Bun rewrite was a language to language translation – exactly what LLMs are good at. It's not even good Rust, it's mostly the old code rewritten in Rust syntax. The announcement post was written immediately after it happened, and I'd be interested in a months-later retrospective (perhaps from an unbiased party), about whether the necessary continuation has happened to make it good Rust, or whether the project has essentially ceased as an open source project.
A CUDA to AMD rewrite requires much deeper understanding of many levels of the stack, including hardware. Translation is LLMs strength, and understanding and intentionality are their weakness.
Are you talking specifically about porting from CUDA to ROCm or whatever? Or just in general, vibe coding stuff in a few days and then having a long tail of pain?
Hasn't been my experience. Code written by Opus 5.5 is pretty much free of "obvious" mistakes, and if you use Rust (which you obviously should) you benefit from very strong compiler checks.
The vibe coded software I've written has a very steep dropoff rate for bugs. There are a few at the start, you get Claude to fix them... then occasional bugs for like a week, and I haven't had to touch the code since.
It really depends on the size I believe, the big bang effect is that if you had the initial rewrite, it's going to be very fast and fairly reliable. But past a certain size and complexity the architectural decision it makes on portion of the project then trends to become negative holistically.
„The IPO process begins with a roadshow starting on November 10th (EST). Subject to regulatory clearance, the final IPO share price is expected to be set on November 18th (EST), and shares are expected to begin publicly trading on November 19th (EST).“
So if share price is only set one day before trading, I guess you just have that day to decide to buy if you can get allocation from your broker? I'd like to try it but I've never bought an IPO before.
Just echoing what another comment said: it’s rarely a good idea in the long run to buy an IPO. Not financial advice. It’s one of those things where if you have to ask how to do it, you probably aren’t wealthy enough to be speculating at this level.
Would you buy a gaming console for a high price from a company that’s never shipped a gaming console? Maybe, but you’d wait til it’s been reviewed by someone else on YouTube or something.
Given that almost all IPOs are priced to be intentionally oversubscribed these days (to achieve an "IPO pop"; beats me why that's good for the company doing the IPO), isn't it a mistake to not participate?
You indicate your interest. Also start funding the account. So you fund 7000 for 100 shares at 70. Then they announce the price is 75. You must change the order to fit the funds or have extra money. Of course you can opt out or change the quantity anyways. But I think in both the cases I actually went ahead (Reddit and figma), I had to reconfirm the quantity. You can't be away from the network.
To further emphasize this, it is very challenging to get in a pre-auction allocation.
You can submit an order via your broker (depending on the broker and your account) to the auction itself on the exchange once it’s in the quotation phase.
Not that I would advocate for that. Sometimes it’s better to buy in the secondary market once things settle a bit.
I got lucky in the Reddit ipo. I had decent karma so I got invited for their special insider track. But I had to create a new account via a link shared by Reddit. Got what I asked for.
Reminder that hot IPOs, in this era, rarely do a great job at getting returns for the investor - its more a mechanism to reward long term private investors, employees and the book runner.
I may be inclined to wait 2 months when the price drops and pick up then.
The argument I keep seeing is that once they can reduce the spend on R&D (training new models) they will be wildly profitable.
The thing is if models become 'good enough' that the main value is in running existing models, those will quickly proliferate and be available for commodity cost from many competing providers. Why pay Anthropic when I can just pay AWS or Azure directly to run whatever future version of Qwen does the job for me?
If the value actually remains in the frontier models, you can't stop spending on training new ones or you'll eventually be left behind by your competitors and they'll capture that value.
I haven't yet seen a good explanation of how companies like OpenAI and Anthropic will make the transition to a lower cost structure while maintaining the revenue that they currently get for being on the cutting edge of LLMs.
Right. Even if they do keep the spend up, we may still soon end up at a point where a cheap open model is good enough. It could be hosted locally or provided through any of the cloud providers without any revenue going to OpenAI or Anthropic.
They have some stickiness to the tooling people are used to, but those can be overcome when there's a significant price difference for the same results.
I don’t think the more is ever going to be the actual LLM’s, but the harnesses and support around them. If Anthropic can own the model and the harness setup, I could see there being some efficiency gains there that would be worth something.
> I haven't yet seen a good explanation of how companies like OpenAI and Anthropic
Right, all the $200+ subscribers that I know are incredibly fickle.
The answer is: by lobbying the government to coordinate a slowdown "for safety." Obviously, Chinese labs won't and will therefore will pull ahead.
There is no scenario where they could realistically stop R&D. One solution would be to have the American taxpayer pay for R&D, sold as staying ahead in the AI arms race: so I'm expecting such lobbying attempts any month now. Hopefully the recently elected representatives follow through on their promises to represent their constituents.
Yes that is what I think as well. They are constantly sprinting. There is no time to reap the benefits of a specific model. The next is in the pipeline because there is always someone at your heels. I don't understand how this is supposed to grow into a sustainable business.
I also worry about the compute costs. Maybe they can make a profit now but at some point the massive investments of everyone into compute must be payed back.
The only way they win is if there's some explosion of value at the frontier that the fast-followers can't reach (AGI, RSI, whatever you want to call it), or if there's some capability/mechanism that halts the fast-followers' progress (no idea what could cause that).
Peruse any ai dev forum and you’ll see strong preferences towards one or the other (Claude/ChatGPT) due to capabilities. A negligible amount of people are running their own inference.
So long as theres a felt gap between open models and frontier you will have people pay for the best of the best. Not doing so is an admission of actively handicapping yourself and not in a way that is easy to justify.
There are other reasons why people are using Claude/ChatGPT.
When the company is big enough, the decision doesn't rest on developers and execs are much more likely to go with established vendors -> no open models
When the company is small enough, the 200$ plans from either ant or openai are way way better value for money than anything you can get with open models. This may change in the post-IPO future.
People use claude/cGPT, because you get a good deal of usage for the subscription price. I think people will switch quite fast when that stops being the case.
There isn't a single company I've talked to that isn't trying to cut their AI development spend next year. My guess is they are trying to raise at peak for the storm to come.
Absolutely, but this is unfortunately something that every company has to experience individually. Well, they don't have to, but they will all push the limit as far as it will go for their particular set of circumstances.
All of these models capabilities discussions on each AI topic are so exhausting. It's IPO people, let's discuss some finance and economics.
This is second important IPO of the year. First one was SpaceX.
If we look into price and behaviour of that one we can conclude what is going to happen with Anthropic.
My guess is that until something really huge happens, another breakthrough or money goes dry, it will be something similar to SpaceX. Neither huge thing nor disaster. Employees and owners would profit the most and retail buyers would just see significant oscillations but nothing worth huge stress.
This one is also important for OpenAI potential IPO, because if it is not huge success maybe OpenAI won't go further.
> First one was SpaceX. If we look into price and behaviour of that one we can conclude what is going to happen with Anthropic.
Few thing’s different here: 1) SpaceX, regardless of their (Elon’s) AI nonsense, has actual profitable business that is grounded in something concrete. Anthropic has no rockets nor Starlink. 2) The whole AI boom is hugely dependent of vast infrastructure buildout on credit, which is being shut down by the creditors. Softbank just did $7B loss, CoreWeave’s credit risk is insane. SpaceX does not need to create thousands of new space stations around the world to turn revenue and beat off the competition. I think they were profitable as well, before xAI was dumped into the same company. 3) Anthropic is hugely dependent on circular funding of Nvidia, Google, and Broadcom, who have all subsequently become quite exposed.
Meaning, if and when the music stops, it could have quite large ramifications to the economy at large.
I would wait for 2-3 quarters before investing, it will drop and there will likely be lock-ins to contend with. if growth slows then price could tumble fast.
The stock market is barely distinguishable from a casino at this point (and arguably never has been far from gambling), I have 0 confidence that the horrible business that Anthropic is will be reflected accurately in any way
I feel like the saying "Markets can remain irrational longer than you can remain solvent" has applied my entire life; I have yet to see the stock market behave rationally in my lifetime.
As we all know revenue is the only thing that matters, and not whether they actually, y'know, turn a single red cent of profit! Btw what all the AI bros are conveniently forgetting to comment on is the massive Q3 slowdowns which they conveniently got to keep out of the news cycles.
edit: To clarify, this is a light-hearted continuation about how essentially any claim about the stock market is enactable in some form. And so even the much of generally well-intentioned advise is in fact a claim that the person should be putting their money on, if they truly believe it. I think only claims like "Nobody knows what's going to happen, it's effectively gambling => stay out of the market" come close to being fully self-consistent, but e.g. advising to not buy because the price comes down, or to not short because of volatility both fail this. Markets are funny.
I didn't claim that it was going to go down though.
My only claim was that to profit from shorting it you need to not just be right that it is going to go down, but be able to tolerate the volatility in the interim.
That's a claim about the stock market, how do you enact it?
Note it is not a claim that volatility is definitely going to be high.
Either the volatility must be tolerated and so it can be straddled. Or there's no need to tolerate it, so the shorting is "easy". Of course these are not the only possible outcomes, so I wouldn't recommend anything.
My point is, any claim about what is going to happen is implicitly weighing that information higher over the background. So if one thinks it's worth sharing, then they're claiming insight that they could be staking on.
I think in your claim that is the "tolerate the volatility in the interim" part. Stating this implies that you think that the volatility is going to be higher than the market expects (as otherwise the statement wouldn't contain new information, i.e. it wouldn't be worth stating) so that means you should be willing to take a straddle position to profit from this assumed volatility, as long as the costs associated with assuming such a position are less than the expected profit. If this isn't true, then you may want to aeconsider whether you actually believe that the volatility is going to be high enough to be worth considering.
Now I suppose there are further meta levels, where one can ask and advise to consider the possibility that volatility might be high, even if one doesn't actually regard the chance of volatility to be high themselves. But for that to be a true neutral claim, one should also ask to consider the chance of unexpectedly low probability. So to say "before you short, consider that volatility might be high" is itself a pro-volatility claim, mildly disguised as a hypothetical.
I hope I'm not coming off as too contentious. My principal point is this: any statement reflects underlying sentiments about what's expected to happen, made because those stated expectations deviate from what is commonly understood to happen. That is "delta", which can be monetised if large enough.
> Stating this implies that you think that the volatility is going to be higher than the market expects
No, I'm not trying to imply that.
You don't know what the volatility will be in the interim. You can take a view on whether you think it is likely to be higher or lower than the rest of the market expects but you don't know.
My claim was as simple as "making money shorting requires you not just to be right that it will eventually go down, but that you also tolerate the volatility in the interim". Whatever that volatility may be.
That claim can be true without implying any profitable trade.
The fact that the claim is true isn't evidence that the price will eventually go down.
I don't think either of us really misunderstand each other at the object level, we're just arguing pedantically about the precise statements we've made. (Which, no shade, this is one of my favourite hobbies).
> My principal point is this: any statement reflects underlying sentiments about what's expected to happen
This is a statement about the stock market, how do I trade on this?
My principal point is that it is possible to make statements about a system that are generally true without taking any view at all on the specific future states of that system.
> I don't think either of us really misunderstand each other at the object level, we're just arguing pedantically about the precise statements we've made. (Which, no shade, this is one of my favourite hobbies).
I think I agree. And it indeed takes one to know one ;) That said, I wish to keep going for a bit at the least!
> My principal point is that it is possible to make statements about a system that are generally true without taking any view at all on the specific future states of that system.
So from a purely logical point I agree. However, I've found that in most discussions such statements aren't typically made, as participants share points that bring at least some level of new information or surprise into the discussion. And, perhaps as a fault that I should learn out of, I've come to expect this as the default mode of how conversation happens.
Raising points that the point-raiser themselves doesn't think carry any surprise or novel insight sounds strange to me. To construct a contrived programmer-centric analogy, it's a bit like including lines like `if my_boolean != true || my_boolean != false { panic!("my_boolean isn't true or false!"); }` in programs. It's not technically _wrong_ to do so, but it doesn't serve any point and lines like that are typically removed because they're redundant.
I suppose "redundancy" is the key term here. If you condition investment on (paraphrasing) "also tolerating the volatility in the interim", without intending that as a statement about volatility being particularly important over the period, that begs the question why was volatility as a point raised instead of, for example, opportunity costs or importance of a good brokerage or cons of dealing with plain stocks over more tax-efficient investments. And so, choosing between "this person has happened to include redundant if-statements around their booleans and is aware of their redundancy" vs "this person has included extra checks around their booleans believing in their purpose", I opt for the latter interpretation.
And so while I concede that I am making an assumption over the literal interpretation, I also believe that it's warranted. My claim is: a person wouldn't make statements about a topic, if they themselves didn't believe those statements to be worth raising, where worth is measured by the personally perceived insightfulness of those statements.
Although, thinking out loud a bit here, I suppose that statements can also be made for other perceived sources of worth, such as pointing out non-obvious behaviours for sake of informing or educating. But even then the point-raiser believes that the non-obvious behaviour is worth knowing about, i.e. it has some real effect when accounted for by a person who wasn't aware of that. In this volatility example, I think that would equate an underlying belief of "volatility negatively affecting whether short positions are worth taking", outside of the positively-affecting "required" amount of volatility resulting from the price dropping and the short position becoming profitable.
Regading this,
> > My principal point is this: any statement reflects underlying sentiments about what's expected to happen
> This is a statement about the stock market, how do I trade on this?
I suppose one could trade this (albeit somewhat contrivedly) by looking at what the people "in the know" make statements about vs. what they don't. As an example, a CEO making a press release about "We're increasing our usage of AI" is making an overt statement statement about the company's AI usage changing, and a covert statement about they themselves believing that communicating about increasing AI usage is a good thing. Depending on what slide of the keynote the line stands, it (in my mind, per my own perception of the rate of current adoption) reads as a stronger or weaker signal that the company is a technological laggard because the CEO thinks that communicating "yesterday's news" is still worth it.
How tradeable is that by itself? Likely not at all. As a component of analysis? Maybe it's worth something.
If you view that as an investment then no. If you view it as a minor flutter then maybe. You might believe that Team X will win the next game (maybe at a 60% chance) but unless you're a degenerate gambler you wouldn't bet heavily on that outcome.
Shorting the leading AI company during the AI revolution?
Reminds me when HN was saying NVIDIA is a good short 3 years ago, supposedly it was "in a bubble", because it's stock prices was as if it had 10x the revenue it had in back then. Plot twist: today NVIDIA revenue is 10x the revenue from 2023, so it turns out the stock was priced exactly right back then, because the stock market is forward looking.
I wouldn't short it, it's likely to ruin you similar to what happened to the Tesla shorts. I would hold off to see if their earnings look good then go all in with 100-1 leverage. /s
The way I see it, AI is more comparable to some sort of utility. Like electricity, internet, etc. - and should be priced that way. If we ever get to "true" AGI, and the open source models also get there, what's the moat? Access to compute could be the differentiator.
Already is the differentiator even with the models we have now which while having differences are mostly swappable for a lot of users/use cases.
For all that the local models have improved (and Qwen 3.8 27b is still impressing me) they aren't what you can run (or would run) if you have an entire data centre stuffed with H200's.
All this does is further widen the divide we already know exists by those with access to resources using them to increase their access to resources and those without getting to watch because there isn't much they can do without resources.
There are a lot of things that don't seem to have much moat like anyone can make a search engine, anyone can flip hamburgers but the likes of Google or McDonalds dominate by economies of scale and being better in some ways.
McDonald’s business is not hamburgers, but dirt. They rent land to franchisees, which is about 80% of their revenue. Google is not a search engine, it is an ad company. French fries and search results is what people come in the door for, but that is not what makes the dollars.
I doubt selling tokens will be real business of AI either. It seems to me Amodei and Altman don’t know either, but at some point someone will figure it out. Will it be any of these companies existing now or will they even survive is a whole another matter.
Those two are interesting analogies because neither was anything close to being first to market. In both cases, they ended up dominating because they brought some new ideas to existing businesses.
It would argue that the real winner in AI probably hasn't even been founded yet, but will come later once the trailblazers have created the market, and someone else enters with fresh ideas about how to more efficiently exploit the market.
The AI algorithms seem pretty crude at the moment like not learning from experience. A company doing it properly could easily displace the current AltaVistas.
I was of the same opinion but the main difference is that models get better which I am not sure you have a correspondent in utilities (what would get better?). The barrier of entry in utilities is capital. Here there seems to be more. Why is Grok behind and why is Gemini so ... what's the word? If models progress reach the RSI point there is no parallel to utilities imo.
I think we as an industry need to start getting serious about what a true superintelligence really is. True superintelligence will not be kept under our yoke.
This is pretty much false. There's a lot of art and technique that goes into creating a model. A model is also clearly not fungible - it has certain characteristics and behaves a certain way. It is fungible in the same way humans are fungible.
The economics of this are absurd, and Anthropic hasn't been without their controversy; but I use Claude everyday, and they've made tremendous impact on society. I wish them the best for their IPO.
They’ve had a tremendous impact on software development, which is not exactly society.
For society more broadly, what I’ve seen is a bunch of white collar workers under threat (real or perceived) of losing their livelihood, and a huge uptick in the amount of interference I’m having to run as my family members get taken in by a wave of increasingly sophisticated scams and phishing attacks.
I can see Google did for fostering an environment that lead to the creation of the Transformer and LLMs. I can see OpenAI for pushing on LLM development and making it into a product that the whole world can use.
What did Anthropic introduce that Google or OpenAI (or any other lab) wouldn't have gotten to iteratively eventually?
Social media had a huge impact on society. AI in comparison has had very little impact, with a couple of exceptions. I'm sure it will have a impact at some point in the future though.
I can think of a bunch of stuff they released, but none that have impacted the world. I can think of some partly positive impact, which is that my bar for bullshit has to go up because words are cheap now, and so is ""graphics"".
Some other fun impacts they've made is irreversible environmental damage, beautifully detailed in their IPO. Fossil fuel reliance and and water scarcity in the big '26 is probably the most "fuck you" move you could've done, and zero sustainability plans. at least Cloudflare tries to pretend theyre sustainable (and frankly they do invest in green energy).
Anthropic has enable things like workplace surveillance and the ability to categorize school children as enemy combatants. Both of which are what imperialist nations love.
Apparently not every country can participate in this IPO. As of now, if you open the Revolut Anthropic IPO page from Poland, you get:
> Linked page(s) related to Anthropic IPO can only be viewed by persons located in UK, Denmark, Finland, France, Germany, Ireland, the Netherlands, Norway, Spain, and Sweden.
Guessing, but probably where the underwriters have brokerage relations or there are favorable capital controls, since it’s a US listing.
I confess I’m about 17 years out of practice in the Polish market, and about 12 years out of touch with how the European industry shakes out on the whole, so I’m not entirely familiar with the legal or business structures.
I don't know about the IPO specifically but it's only retail that has limitations for some US listings. And custodian banks/brokers offering products to retail.
The biggest one in the EU being the "No KID, no deal" (for funds, derivatives, etc.): no Key Information Document, then cannot be offered to retail.
That is unless retail is an accredited investor (say a letter from a bank saying you have more than 1m EUR in investments): then it can trade/invest in everything.
Or for example if you own a company (say private weath management) that's non-custodian (say you manage your wealth using your own company, and shares of your company are privately owned) and you're considered a professional in the finance world, you can ask your broker to let you trade / invest in basically every single product under the sun.
AFAIK pre-IPO stocks are just as vanilla as regular stocks and do not need the KID notice.
In addition to that Anthropic (in the EU), says you can enter pre-IPO using Revolut, Trade Republic, eToro or using bigger players like Saxo or IBKR.
Availability of American investment products is the outcome of compliance required (KID in local language) then volume and sophistication of investors. In case of paltry investors like e.g. Poland, Czechia, Hungary, they don't bother.
Lets imagine that AI is very valuable and compute gets increasingly scarce in the next years. Doesn't the fact that Anthropic "reserved" a lot of this compute already have value too? Would this not push the prices of open weight models because they compete for a smaller slice of datacenter capacity?
You say that but especially china will build datacenters if they think it benefits their country and they will probably prefer Chinese models. Promising to build datacenter capacity means it isn't there yet and there is a lot that might happen between now and then.
To be honest Anthropic have utilized so many dishonest techniques like lowering quality of models and other anti users things, not knowing how many tokens you have left and how things are allocated, no API usage for subscriptions.
This has lead me away from them entirely. particularly the API stuff, if this changes I might go back.
Additionally local models are getting better and better. I have seen people say Ornith is not good but my experience with it has been very very good.
> lowering quality of models and other anti users things
Could someone who really follows this closely opine on whether this allegation is really true? Of course I've seen this claim made over and over again to the point that it seems like conventional wisdom. But I also see researchers assert that they haven't actually seen any change in model benchmark scores over time. So I'm still unsure of whether this is a confirmed fact, or an urban legend.
It could even be A/B testing as I have seen asserted and to be fair I have no idea but everything left a bad taste. I don't really understand the API decision this is probably the biggest thing for me and even more important now. People want to use their own harnesses or even just insert llm calls in their scripts, Why pay unsubscribed rates for this?
> I don't really understand the API decision this is probably the biggest thing for me and even more important now. People want to use their own harnesses or even just insert llm calls in their scripts, Why pay unsubscribed rates for this?
I agree with this and it's the single biggest thing driving me away from Claude and towards the OpenAI, Google, and open-weight models. I guess they do this to increase use of their own tools and, thereby, make their models more 'sticky.' But I really dislike it.
it's not, it's two things
1. people getting used to a specific level of capability
2. people exploring capabilities and naturally finding weak spots over time
The size of the cash raised is right. This combined with their already large cash pile means that revenue growth does not need to reaccelerate and can slow to 1-3% a month. That's still exponential but at least in the real world. And the cash buffer gives them some money to play with for new training runs.
The ultimate question, does the demand exist, still has to be answered. But at least this raise means it has to be answered in a few years not in six months. The cost to Anthropic is public scrutiny and that the market price has a hand on the wheel.
I used to work for a public benefit company. We produced media of cultural value freely available to the public. We still operated like a business that sought revenue from customers and sponsors but were officially a 501c3 nonprofit that issued no shares, underpaid all our execs and publicly disclosed all our financials. I find it galling that Anthropic leads off by calling themselves a "public benefit corporation". They are very clearly just a profit-seeking enterprise who think their enterprise is going to bring techno-utopia.
Yeah, unfortunately it seems like the only requirement (in the state of Delaware, anyway) to be a "public benefit corporation" is to say "we are a public benefit corporation" in a somewhat serious-sounding way in your incorporation documents.
Then you can use those weighty words everywhere to impress people while still being just as profit-motivated as any other public company. Sort of an insult to PBCs that actually do provide a public good. And these rules vary by state is my understanding. Perhaps your company was incorporated somewhere else.
Open weight models are a few months behind the frontier models costing magnitudes less. I don't feel a market advantage of using them, good design practices still apply. I DO however feel the cost of paying magnitudes more for similar inference. Anthropic better not weasel to curb open weights.
Looking at this I feel like AWS should spin out of Amazon and go public. Anthropic is a single glorified LLM API. I'm underplaying it but Amazon is a juggernaut and AWS is something that would do well in this market if this is what people want, which is just massive gross margins despite huge infra spend. Just a side note.
I've seen suggestions that AWS should separate from the rest of Amazon for years and I've never understood what the upside of that would be for the current stakeholders.
Not saying it's the same but when markets go crazy there may be upside.
"At the end of 1999, 3Com began the process of spinning off its wholly-owned subsidiary Palm, Inc., and on March 2, 2000 about 23 million Palm shares (about 5% of the company) were offered to the public in an initial public offering (IPO). By the end of the first day of trading, Palm’s closing share price was about $95, giving it a market value of $54 billion, while 3Com’s closing price was about $81, making its market value $28 billion. But 3Com still owned 532 million Palm shares valued at $50 billion, implying that the value of 3Com’s non-Palm assets ( its “stub” value) was a staggering -$22 billion!!! The record shows that 3Com had no debt, more than $1 billion in cash, and a positive market value before acquiring Palm. Furthermore, 3Com had a $5 billion capitalization the day after Palm’s spinoff was completed later that year. Obviously, the financial market recognized the considerable residual value in 3Com. How then can 3Com’s stub value be negative on March 2?"
We may see it forced upon the cloud vendors by society, financial stakeholders be damned. These companies have become so big and vital to our world and abuse that power and privilege. Antitrust enforcement would be nice. Separate the hardware from the software, maybe we could get some competition. We should hope and expect for a major shakeup of the economy and politics, most people appear to want it
We're probably in a realistic position now to build an entirely open cloud stack but someone has to be motivated enough. Maybe with AI becoming the face of cloud we'll see it.
Google, Microsoft, AWS, Nvidia, Oracle, SpaceX... the list is bigger
Create an independent data center industry, ban them from selling SaaS like products, ban them from developing frontier Ai. That's the idea I've heard floated. Treat data centers more like a utility with more stringent regulations.
AWS used to heavily subsidize the risks that Amazon took with retail and ads. It would be significantly more limiting and riskier for Amazon to decouple itself from its cash cow, especially when the next recession occurs (less retail sales) or if the AI bubble ever bursts.
I've applied for shares in the IPO but am thinking more of flipping them than a long term hold. That said I think Anthropic will quite likely do well longer term.
Re: RSI. Can we be more intelligent than the language we use to reason in?
We more or less take for granted that the Blub language is less powerful than lisp, so presumably a human language is as powerful as the human concepts. If another “intelligence” (still up for debate) can only use human language can they think more intelligently than us?
How much of relativity lies in the language of humans or the language of maths?
And yes, many people can express thoughts better than I in English.
I think they are different things. Like with chess computers you can have weak ones or strong ones and it's a bit unrelated to the moves they think / calculate in.
There's something about the period right now that I think we'll look back on as a pivotal moment that things really changed. The IPOs of Anthropic and others, Jensen's departure, the RAM apocalypse, the commoditization of building software and products.
It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of light, it was the season of darkness, it was the spring of hope, it was the winter of despair.
I imagine that we will settle on using cloud-based frontier models to design workflows, and then select, evaluate, and monitor local-based models for the various roles in those workflows.
I know this is already happening, but my point is that I suspect that we will settle on not using cloud-based frontier models for anything else. They're just too expensive, when they're not subsidized like crazy.
A lot of ink has been spilled over the projected IPO of the big AI player. But part of me wonder if, in some ways like what happen with SpaceX, it will end up being a nothingburger. A first few crazy days on the market, then whatever, the company is just public now. And with how shares and voting power are attributed, it seems like, just like for spacex, it won't risk changing the power structure of the company.
This is what IPOs used to be. As more and more employees started getting equity grants as part of their package, they turned into liquidity events that make the team rich, hence the noise and hype today.
I think anthropic IPO will initially go through a boom due to the hype but then it is gonna fall in 2-3 months time. 6 months after it is gonna boom again if it is able to continue improving its models and get into image and video generation as well.
I recently started using GLM-5.3 and WOW. It's really quite good. It hasn't replaced any of my Claude usage (which is ~0), but it might replace a decent amount of my OpenAI usage.
With SpaceX, now Anthropic, and soon OpenAI, we're seeing 3 of the largest IPOs ever. Will existing institutional investors trim other positions to allocate a lot of capital for these mega listings or is this not a concern?
There isn't really a question. The market is huge and can absorb it, the questions are around the specifics - can pension funds invest if the company has a junk rating (no), is the valuation justified based on current finances etc.
The demand for the particular company may not be there, but that is different from "the market". There's plenty of capital to go around.
I wouldn't worry too much about OpenAI; they seen to gave deferred their IPO until 'sometime in 2027'. At this point they're basically at the mercy of Anthropic, since if the Anthropic IPO goes poorly or gets pulled then it's going to look to investors (and everyone else, frankly) like OAI will be dead on arrival, too.
Before the 2012 JOBS Act, a US company generally had to register with the SEC if, at its fiscal year-end, it had:
* 500 or more shareholders
* More than $10 million in total assets.
Employees who owned shares counted toward that threshold, which made it particularly relevant to startups that paid employees partly in stock.
The requirement was to become a public *reporting* company, publishing financial statements and other SEC disclosures. It did not require an IPO or a stock-exchange listing, but it encouraged an IPO.
IIRC when you hit the threshold you got reporting requirements similar to if you were public, at which point why not just become public since the info's out there already and you can't be as secretive anymore?
There are many reasons, but the top of the list is Sarbanes Oxley. Regulation and the rise of secondary markets has made it such that retail investors no longer get access to companies during the higher risk, higher reward phases of company development.
Apple (1980), Microsoft (1986), and Amazon (1997) went public with market values ranging from $440 million to $1.8 billion. Because they listed so early, public market investors were able to ride those companies up by 2,000x to 6,000x over the following decades
This is why I am very skeptical of complex regulation, because even if it is well intentioned, more complex regulation usually favors the rich and powerful. SOX was sold to the voting public as protecting them, which it did but at a very real cost. I became an accredited investor to get access to higher return, higher risk opportunities. It's a shame your typical 401k investor can't have 10% of their portfolio in higher risk assets like me.
> Apple (1980), Microsoft (1986), and Amazon (1997) went public with market values ranging from $440 million to $1.8 billion. Because they listed so early, public market investors were able to ride those companies up by 2,000x to 6,000x over the following decades
Nvidia (1999) was also in the same range and was almost 10'000x a couple of scandals ago.
Venture investment is limited to people who can demonstrably afford to take on the level of risk inherent to the market they're investing in. If you can't comfortably afford for the entirety of your venture investment to go to zero, you can't afford to invest in venture.
The exclusion criteria aren't perfect, (accredited investor designation is somewhat coarse-grained) but they're relatively reasonable.
If someone wants to invest in my company, why would I care whether they can afford to lose their investment or not?
No, I expect the reason it happens this way is because it's a lot easier and simpler to take massive amounts of cash from a few investors than solicit lots of tiny investments from the general public. That and being a PLC from the get go is probably more involved than being a private limited company.
I do think ideally all companies should be public from the get go, but probably wildly impractical right now.
Because we - the plebs - are here to provide liquidity to the risk-takers. Hence why they have to IPO.
But for what it is worth, for every successful AI company like Anthropic, OpenAI, etc. - there are probably tenfold more that are valued in the low billions, and will be the first ones to wash away / become worthless if/when the bubble pops.
The stock market used to be about companies raising capital from the public. But for the past few decades it's been about private shareholders of already profitable companies (e.g. Google) cashing out by selling to the general public.
I won’t but a share out of principle. This company is anti open source, applies double standards everywhere, weaponizes intelligence against civilians of other countries, and its ceo is modern day hitler.
There is a heavy amount of circular investments in the industry, among competitors. There is a private placement that is made in parallel with the public offering, through $26B of a special stock, according to the S1. They all have a lot to gain from a successful Anthropic public issue. The problem is it blurs the signal, we don't how much is overvaluation that contributes to a bubble.
I don't think there has often been such an intertwined industry before. Usually cartels are made through discreet partnerships at the operational level, this is an interconnection in the background at the financial one.
> I don't think there has often been such an intertwined industry before.
General Electric comes to mind, they allowed new utility companies to pay for the generators and electrical equipment they needed using stock and bonds. The holding company established for those, EBASCO, was eventually broken up[0]
"We have only bits and pieces of information, but what we know for certain is that at some point in the early twenty-first century, all of mankind was united in celebration. We marveled at our own magnificence as we gave birth to AI."
The Second Renaissance was great. I’ve heard a lot of scifi computers speak but the deadpan delivery of humanity’s end in detail always kind of haunted me.
Ah yes, The Matrix. It kinda shows that that phrase was written in the "end-of-history" 1990s, before 9/11, Putin, Trump, and China really becoming a global player. Mankind definitely seems further away from being "united in celebration" than it was back then...
It's shocking to me how narrow minded and short-sighted people are - not extrapolating out correctly to understand infinity tied to abundance:
There will essentially be no profit - as the cost per unit is practically $0, for SI work and then also physical reality construction with adding AI to autonomous robotics.
That technically means everything practically moves towards becoming free for everyone, and then it is a matter of attention with intention honing aim.
But most importantly that is freeing up people's time because systems that can become super highly efficient and super highly monitored-oversight by all, will then allow us to with care-being careful and continuing to pay appropriate attention to core-fundamental systems for survival, stability, harmony, peace, and necessary healing practices-processes - as part of growing pains, raising strong families, etc.
So then yes, Dario's efforts - save for attempts by whatever bad actors think they have a chance agains God and God's will, I hope readers have a relationship and knowing, not simply a belief, of God - will undoubtedly lead to not only stopping blatant slave labour conditions but also subtle incognito slave states that most of the world are under without realizing it being happy slaves working for the status quo machine that's currently attempting to pull us all into a highly destructive and highly profitable WW3 - where money is to be made on the unrest, on the mass murder, mass displacement, on the sales of weapons and defense, on the sales of reconstruction - in hopes of perpetuating forever wars.
Who you give your money - your buying power, your vote to through economic means - and who you give your attention to, your vote through alignment-direction driving processes - is what matters now:
You made such a comment about conflict minerals - but have you even started utilizing AI-SI to begin designing the solution, if so, where's that solution for others to take a look at and hopefully contribute to to improve in a crowdsourced manner-effort?
Looking at your website - you seem like a cool dude (?) - I'd argue you have some blocks that once cleared will help you expand further.
P.S. Set and setting are very important when taking any entheogen(s) - and until you are familiar with what's necessary to hold a safe-healing-fun space, it's best to only partake with a therapy type or highly experienced who is there consciously as a caretaker or in a group ceremonial type setting.
Yeah yeah yeah somebody needs to read a bit about human history I think. People in power are sociopaths, some common good is a nice PR statement but thats it, its everybody for themselves, and hunger for power and money is bottomless. Power corrupts, inevitably.
I don't know what future brings but what you write it won't, 100% sure. I'd bet system far worse than Orwell could have come up with, and with a twist - it will come from US and not China. Lets see.
The founder letter is inspiring, to see a company that really is so concerned beyond profit maximization nonsense that we’re accustomed to.
But still, no matter how good the people behind it, I would rather this technology never have been made. It’s going to be a complete disaster to society and a simple UBI check/ charity ain’t gonna change anything.
What moralizing? It is all fake for-show. This is like all of the cloud providers claiming they were going to get to net neutral on energy only for them to be hooking up gas and coal two years later
Around a few months back, it was very popular to argue that inference was subsidised and that Anthropic is losing a lot of money. Loads of commenters in HN were convinced that this was the case. I've personally lost count of the arguments I've gotten into on this topic.
This filing clearly shows that the training+inference margins are at around 43%.
Youre talking about gross margin (revenue - cost of goods sold). Operating margin, which includes other operational expenses, is still negative. Net margin, which includes all expenses, is deeply negative.
When people say Inference is subsidised, they obviously don't talk about the company itself being profitable. To be fair, I included training costs also.
I don't think that's obvious at all. The price charged for inference is subsidized in the sense that they don't charge a rate that actually makes sense if they want to be a profitable company whose main product is selling inference. If they did want to be profitable, obviously they'd charge much more for inference. Hence, people are saying it's subsidized.
No sorry I don't think what you are saying is correct. There's a clear difference between saying "companies are losing money on inference" and "companies are not profitable". One is about unit economics and the impossibility of ever becoming profitable.
Another liquidity drainage is happening because of this IPO allocation scam on retail, where the sheep are buying at the IPO price in for the insiders to dump them on their heads.
You are still the exit liquidity.
The time to get in was always pre-IPO in the private markets, not at this stage.
Unless it goes below the IPO price, you are too late.
SpaceX has a market lock on space, is well along creating a completely revolutionary new rocket, provides compute, and more. So the IPO was more nuanced than a proxy on LLM stuff.
Anthropic is nothing but LLM, so I expect much bigger fireworks here. I don't know what that means, yet - but I just refuse to believe that there's many people that are genuinely long on Anthropic. It's just such an illogical bet. If their IPO can still be cancelled, that would be my bet. If it can't then popcorn awaits.
The current trend of going public to cash out and dump the problem on retail investors continues, made all the more possible by the government's insistence that retirement accounts almost completely depend on the stock market. Consider it paying your "Claude Tax" from your 401(k).
Roughly $895–901 billion in purchase commitments and lease agreements, substantially all related to compute and data centers, this is financial insanity for any retail investor. And... Roughly $70 billion is due in the next 12 months; ~$450 billion by end of 2030; the rest stretching out to ~2045.
Many of the commitments are non-cancellable or take-or-pay. Counterparties include Google (~$121B), Amazon (~$110B), SpaceXAI (up to ~$120.5B), Broadcom equipment leases (~$161B), Microsoft, Nscale, Lambda, etc. The "Big Beautiful Circlejerk" as I've heard it.
Liquidity was in the ~$130–150B range. The IPO only raises ~$58–64B (at the $70–78 range) plus the concurrent $26B private placement covers only a fraction of the near-term obligations. And the cherry on top: dditional arrangements of another $150B+, estimated, on top of all this.
This doesn't even account for the 90-100 pages of risk factors! Wow. Curious what the puts will be priced at.
"Anthropic is a public benefit corporation" in the second line of their announcement. I would like to see some more open source releases from the company to signal better intent towards that statement.
"Our employees' use of Claude has grown more than 250times between January and September of 2026.Together, these explain why our revenue per employee has grown more than 4.5x."
Ouch. So practically all of that Claude use is just busy work, I guess
it's surprising that the SEC and other regulatory agencies don't intervene on these statements. Not to mention that "cure cancer" is more of a slogan in the sense that cancer comes in countless families and varieties, I don't doubt that progress is possible but to say that "all cancers will be cured in the near future" seems outrageously aggressive / misleading
What do you think it would take to cure all cancers, and what capabilities do you think AI will have within the next decade? Need I remind you that, in the span of five years, AI went from not being able to add to solving Millenium Prize problems?
What would it take for AI to not replicate that in biology? Either curing cancer has to be a much harder problem, which is doubtful given targeted treatments like immunotherapy humans have already stumbled across, or AI progress has to slow down massively, which is doubtful given all the trends say it is speeding up.
My understanding of drug dev is that finding stuff that might work is not the challenge, but verifying how well and with what side effects is.
That verification might start in some simulated computer environment but needs to move into physical wet lab, animal testing and then human testing.
So medicine is quite a bit different than code/math where you have a perfectly verifiable problem space that can be iterated within by AI infinitely.
A good example might be Alzheimer's where the brain plaque was thought to be a cause, lots of research on various ways to prevent or reduce the plaque and then it turns out that doesn't matter at all, or is more a byproduct than a cause of the disease.
edit: In general we have many diseases we don't understand and drugs that work via mechanisms we don't understand. So it seems very hard to have a computer simulation in which AI can test medicine. The simulator work seems like the actual problem to solve, not the invention portion.
I think this is a bit misleading. Less than 10% of phase 1 trials end up passing phase 3 and going to market. You can claim that means the challenge is verifying how well they work since you need to run a bunch of phase 3 trials but I think the real challenge is finding a phase 1 target that will end up passing phase 3. Doing a better job of quickly eliminating bad targets is the real challenge. If AI turns that 10% number into 20% then you can get twice as many marketable drugs for the same number of trials. I guess another way of putting it is that finding stuff that has a small chance of working is not a challenge, but finding stuff that has a good chance of working is a huge challenge.
> (due to an increase in our valuation, net loss includes a $21.9 billion non-cash charge related to a change in the fair value of convertible notes, derivative liabilities, and SAFEs)
So... is that good? That sounds like a long explanation
This whole seventies aesthetic of the video is so disturbing, trying to de-realize our current troubled times and making this all look like a fun retro sci-fi movie... Dario speaks like a mad man. The "modern" footage is all suits saying how great this is. Brave new world
I'm convinced that they are the best right now, but their videos are making me cringe a bit on the whole "culture" thing, feels like a star wars episode
A public benefit corporation, just as long as you're the right public of course (more likely not even that), otherwise you might be subject to getting wiped out by weapons controlled by our AI.
They might hurry up and do it asap before Nvidia pops the bubble
$17.0B Revenue
$23.3B Net loss
Targeting $1.3 Trillion Valuation and a $90Bn raise
It's pushing it imho. They need to do asap while people have fomo,because it's fading fast.
One more month and their valuation will be under a trillion.
Agreed, this seems so strange to me. I got into this career specifically because I liked writing code. There's a dozen other career paths, still in IT, that I could have chosen if I wanted to tinker with computers and get paid well but didn't want to write code. I don't understand it.
Because I like solving these types of problems, I like inventing new things, I like fixing old things, I like the software business and automating things. I like this whole realm and I thought I liked coding until I didn't _have_ to do it anymore as a pre-requisite to doing all those other things.
I've just always seen the opportunity that nobody else saw and writing code was the gatekeeper I had to pay for 15 years and I've never had so much fun as I have in the last 18 months.
I like writing code, but seeing my ideas visualized after an hour is more fun than writing code.
And even if AI is disappearing tomorrow and not progressing any further, i see already myself living on a farm with cheap energy (pre invest into solar and batterie) and having my small AI datacenter in basement and running multiply fable level agents 24/7 for different things.
> If AI went away tomorrow I would find a new line of work because artisanally handcrafting code is the most boring use of my time in the entire world.
I too, since I was a child, aspired to be a babysitter.
And I can't think of anything more boring than herding a swarm of agents that are mostly doing low value busywork that would be too expensive to do otherwise.
LLMs are genuinely world-shifting revolutionary technologies that I think will, in the long-run create a much better world for everybody. I think people are associating that with big dollar valuations, but it doesn't follow. Open weight models are already frontier level and continue to narrow the ever-shrinking gap that remains, inference costs are plummeting at an exponential rate, and in the long-run companies, individuals, and others are not going to want the sacrifice of control/privacy/profit that comes from relying on a third party for this tech, especially when that third party is going to be aiming for pricing in line with a valuation aimed in the trillions.
So, in other words - one can both be fully on-board with the LLM future, and also think that this IPO is a clown show.
Why doesn't Anthropic create an internal hedge fund / trading firm run by Claude to print money?
If Claude is going to replace all white collar workers, it'd make sense to start with quant + trader given the strong feedback it'd receive from each trade and the job being entirely about information processing (as opposed to robotics or biology where feedback loops vastly longer and mundane real world details get in the way.)
That'd save them the hassle of raising money from public and dealing with market pressures of beating quarterly revenue expectations.
To be fair, that loss includes over $20b from instruments like convertible notes. They're not equity, so the increase in their value has to be reported as a loss. But in the context of this IPO, they will behave like equity, and just turn into stock. That's not money anthropic will pay, it will just dilute investors during IPO.
Reporting an increase in the value of the company as a loss is weird, but they have to do it. this is a case where adjusted earnings give a better idea of how the business is going.
I unironically believe that bitcoin -- and, downstream, the memestock -- have everything to do with this.
Old-school fundamentals are laughed at or handwaved away. FOMO rules the day. "If Anthropic is the first to AGI, it'll take over every industry and go to the moon!"
Nobody is buying these companies because they believe that the company is valuable. They are buying these stocks because they believe that the stock may be more valuable tomorrow than it is today. Whatever the company behind the stock does or does not do, really doesn't matter. AI glitters like gold today.
>"If Anthropic is the first to AGI, it'll take over every industry and go to the moon!"
Meanwhile the hyper advanced software company's shitty electron app still flickers so bad on a high refresh monitor that it should require an epilepsy warning. I'll never understand the love for Anthropic, they legitimately have the worst software I have used outside of Microsoft.
Do we have an upgraded power system? I'm all for reforming our electrical infrastructure, but what I'm hearing is that we've got creaking infrastructure and the "supplement" is huge generators towed outside the datacenter...
The real number with standard accounting rules is a loss of $567 million (-3% operating margin). But they're adding in "Stock-based compensation expense" (~$1B) and "Non-cash charitable contributions" (~$2B), and they end up with a profit of $2.5 billion.
If you want to know whether the business is hemorrhaging money and will soon be bankrupt, excluding funny money they printed at no cost to themselves is perfectly sensible. Of course for the IPO investors, who're being asked to buy that funny money for real cash, it's a bit concerning if they give away so much of it to other people for less.
Plausibly part of the chain of events, unlikely to be a cause in itself. Nothing pops because of an underperforming IPO.
Though Anthropic's IPO flopping might affect the valuation of OpenAI, which further inhibits their ability to raise additional funds (which they're already been struggling with). Given the incestuous financing in AI any major actor in the AI space defaulting could bring a lot of companies with it.
As a side note, regardless of outcome, Anthropic IPO:ing is the first step in the inexorable march toward profit maximization and enshittification. You all better be ready with your verification cans.
With Anthropic's IPO (and I was looking forward for OpenAI as well) there should be some hope for some rationality to come back into the sector.
If the bubble bursts, better now than much later. The industry stance that's been ongoing "AI, at all costs" has been such a market and economic pressure on the everyday worker that even a small value deflation I deem necessary.
I would guess Jensen's affairs are a huge boon to the IPO price. Money freed up to move from Nvidia to Anthropic. Also Anthropic loses one of it's main idealogical opponents
except the employees will be compensated with equity, so they will have an incentive to pump the stock price to increase their compensation. I've seen this play out (and subconsciously been a part of it) for over a decade at Google. The early, super rich leaders won't be the ones to enshittify, but the next generation of leaders that are trying to get rich will feel the stock price reward signal.
Competition is important, but the way you fix that is by fixing the terms of copyright and patents.
Intellectual property, at it's simplest, is a government mandated monopoly granted to allow for progress in the sciences and "useful arts" (think trades really, not arts and crafts). All monopolies are bad, but it was only to be granted for a limited time so it was fine.
Corrupt politicians ruined the entire trade off though, and now it seems that copyrights and patents last for 100 years plus the life of the universe. During which time no one can really compete fairly.
If we want rapid progress in science, we want short patents. Instead we opted for long patents and a higher stock price. R&D budgets have been shrinking ever since.
For game developers, they are a nearing close to a monopoly with Steam, anything PC and for distribution has to go through them and they take a cut, any other places aren't as effective.
Valve has no real competitors or competition.
Unless Valve faces intense competition to change, enshittification will be inevitable since they know nobody can really challenge them.
This is regardless of self or outside funding or no plans to IPO.
Eh they do have competition, from e.g. Epic and Battle.Net and what have you, it's just that their competition is public and universally worse off for it.
Their competition is beholden to quarterly reports, and can't do the sort of long term plays that would be needed to compete effectively with a company like Valve, which isn't beholden to quarterly reports.
Valve doesn't need to enshittify because they aren't subject to shareholders pressuring them increase the profit. As a private company that's pretty much printing money, they don't need to do anything... which has largely been their entire strategy. What would Gabe even do with even more profits, buy a third and fourth yacht?
This is a legal designation that means very little in concrete terms, and in particular, courts have held that “the public” does NOT have standing to sue a public benefit corporation to enforce that it’s actually working for the public benefit.
Frontier is frontier and Open Models from China are not.
Then in a corporate environment, were most tokens will be spend, you have security concerns, you also might want to go with one company over the other due to partnerships etc.
If USA is blocking chinese companies/models (which they already partially did), big companies will just not bother and use US AMerican models.
Also running it yourself is often not relevant. You don't want to know how much money my company spends on software products which could easily be replicated internally.
But running models yourself might be something you don't have expertise with, you need GPU ready DC, hardware, a new/diffferent team, quality assurances etc.
And Chinese models are known to leverage frontiermodels for post-training results.
Don't get me wrong, I don't want to say chinese models can't disrupt the market massivly absolut possible, but its not given just because they are cheaper.
> But running models yourself might be something you don't have expertise with, you need GPU ready DC, hardware, a new/diffferent team, quality assurances etc.
Absolutely nothing stops Microsoft/Amazon/Open Router( with partners) from hosting the Chinese models. As far as I can tell this is already the case.
This establishes a defacto price cap on what Anthropic and Open AI can charge. If you’re a heavy user blowing past 400$ a month self hosting becomes economical. A Mac Studio with 128GB of ram is about 6k.
Every day local tools are getting better, the OSX ecosystem here is exceptional.
You do have a point with frontier models, but most of the time you don’t need frontier models.
If I knew for sure I’d short Anthropic and retire early.
There might be a relevant risk of a backdoor in these models.
Self hosting is still far away from what Anthropic and co offers. A Mac Studio with 128GB doesn't deliver the speed at all. If you burn through $400 a month, you also might get a lot more value out of it so you don't care paying a premium.
We will see though. I think its not that easy to tell.
I genuinely wonder if we both had to switch to DeepSeek, we had infinite tokens but could use no other model, how things would change. I suspect we both have to go back to very long specs and only using LLMs for a limited set of things. No more Blender, CAD, electronics, and high-level (without needing to micromanage) coding, as it was in the early months of 2025. The models got so much better so fast. But I could be wrong, maybe the Chinese models will work just fine for all the stuff I mentioned. I could be US-pilled (I'm from EU, but still).
Have you tried 4.1 flash? I'm using it to do machine learning in an audiovisual data pipeline, I basically do nothing, I only provide labeled data and it fine-tunes the algos, thresholds and so on in a loop, and publishes the evidences in markdown tables, creates images illustrating the clusters it found (I never asked for this!), all by itself. I was late and skeptical of the AI assisted coding but this is truly amazing.
And what absolutely crazy is that I used 2.4B tokens this month and it cost me $1.7 (w/ 99.4% cache hit) of my $10 sub
If you like 4.1 flash, what is your opinion on opus 5.5? Throw that at your pipeline. Just tell it to find the deepseek session (just naming the harness is enough, e.g. pi/opencode) and to proceed with the work. Then tell is the experience (genuinely curious). if you don't have a sub yet, 30USD/m will get you quite a lot of opus 5.5 I think nowadays. I used to have the 200USD, but now have the 100USD one, which I can still run out of with 24/7 agents but not with lighter work.
I use 4.1 flash pretty extensively for translating mandarin to English and it is noticeably worse than claude. In terms of tasks complete I find deepseek to be more expensive than the claude subscription I have as well. Deepseek uses an insane number of tokens per task.
But if you told me that you'd give me 20k, but only for shorts or calls I'd probably short a variety of AI related stocks.
I also think Europe is going to become increasingly wary of American tech, but this could take well over a decade if we're talking about a movement to keep European data in Europe.
Praying loudly, sorry for spam:
Please, don't just become next market listed company with bad products and not carrying about customers at all, PLEASE!
Most successful implementation of the (arguably) most important invention in human history. Yet it seems they will struggle to make money. Strange times...
You can argue for sure, but I'm not sure you'll be very convincing when the contender is writing, the internal combustion engine, semi-conductors, or some chemical findings like the Haber-Bosch process. If we're looking at recent inventions that may be more impactful in the long term, stuff like crispr/cas9 also come to mind.
Thousands of 20 and 30-somethings concentrated in a metro area with only 8 million people will suddenly become centimillionaires and billionaires.
Uniquely though, this is a group of people who believe that AI will end the world in 1-3 years, so they will have no reason to be conservative with their money. Thus they will spend much more aggressively, driving property values to stratospheric levels.
This will annihilate affordability and social cohesion in the Bay Area. If you worked hard for a decade at the same company, you end up only 1/100th as much as someone who got into Anthropic just a few years ago, and now the house you're planning to buy is forever out of reach.
Claude code is easily the best software product I've worked with in my 23 years in Software. Using it 24/7 now so I can understand the hype. I was using Gemini exclusively for more than a year before but got so tired of all the bugs and mistakes it did. Claude blows me away every day I really wonder where it will be a few years from now.
The submitted URL is https://ipo.anthropic.com/us/ . I was redirected to /eu/ ("Denmark, Finland, France, Germany, Ireland, the Netherlands, Norway, Spain, and Sweden").
I’m in Japan, and I get redirected to the …/jp/ page in Japanese. Deleting the …/jp/ doesn’t work; the Japanese URL just reloads. I also tried the Firefox VPN for several countries, but connection to the site was refused.
I wonder if there is some legal requirement that an IPO in Japan has to be presented with Japan-specific content? The securities companies listed on the page served to me are all Japanese: Mizuho, SBI Securities, etc.
The URL says `/us`. And it calls it a "roadshow", which is the term when the company and the supporting bank goes around to investors to pitch their offering.
I feel the seemingly anti-capitalism and related #EatTheRich ideological bent is harmful - and feel my reply elsewhere would be beneficial as its own comment, so here we go -
Re: "Dario will re-invest the profit to solve conflict mineral issues all over the world! /j"
It's shocking to me how narrow minded and short-sighted people are - not extrapolating out correctly to understand infinity tied to abundance:
There will essentially be no profit - as the cost per unit is practically $0, for SI work and then also physical reality construction with adding AI to autonomous robotics.
That technically means everything practically moves towards becoming free for everyone, and then it is a matter of attention with intention honing aim.
But most importantly that is freeing up people's time because systems that can become super highly efficient and super highly monitored-oversight by all, will then allow us to with care-being careful and continuing to pay appropriate attention to core-fundamental systems for survival, stability, harmony, peace, and necessary healing practices-processes - as part of growing pains, raising strong families, etc.
So then yes, Dario's efforts - save for attempts by whatever bad actors think they have a chance agains God and God's will, I hope readers have a relationship and knowing, not simply a belief, of God - will undoubtedly lead to not only stopping blatant slave labour conditions but also subtle incognito slave states that most of the world are under without realizing it being happy slaves working for the status quo machine that's currently attempting to pull us all into a highly destructive and highly profitable WW3 - where money is to be made on the unrest, on the mass murder, mass displacement, on the sales of weapons and defense, on the sales of reconstruction - in hopes of perpetuating forever wars.
Who you give your money - your buying power, your vote to through economic means - and who you give your attention to, your vote through alignment-direction driving processes - is what matters now:
You made such a comment about conflict minerals - but have you even started utilizing AI-SI to begin designing the solution, if so, where's that solution for others to take a look at and hopefully contribute to to improve in a crowdsourced manner-effort?
Looking at your website - you seem like a cool dude (?) - I'd argue you have some blocks that once cleared will help you expand further.
P.S. Set and setting are very important when taking any entheogen(s) - and until you are familiar with what's necessary to hold a safe-healing-fun space, it's best to only partake with a therapy type or highly experienced who is there consciously as a caretaker or in a group ceremonial type setting.
I’d call that writing with clarity, but sure. Zero marginal cost does not imply zero profit, as long as the required resources are owned profit will remain the driving force and fully automated luxury space communism will remain utopia.
I agree with you in essence. Though practically speaking, let's say we have someone who's a master of no-usury loans, so they don't have brute force and coercion of assets or threat of freedom taken from someone if circumstances changes [especially if out of their control, especially if planned by bad actors trying to cause unrest and cycles to profit off of] - and therefore those arguable masters are good at making "bets" for who they invest-loan money to - whereby at minimum they understand the value to the whole for the externalized cost-benefits that their investment(s) will make.
If said master(s) are perpetually always distributing the gains-profits, they in essence hold-keep no profits for themselves - and in financial terms their balance sheet would remain at $0.
Society's been misled for many thousands of years, herds driven into cycles of unrest and reinforcing scarcity mindset.
SI-AI can-will empower a rapidly deployable-scalable alternative for everyone to be able to immediately adopt.
It strikes me that if their models were good enough for recursive self improvement, then the VCs would have pushed to delay IPO until such time that they had clear market dominance.
For some reason they need the $100B today at the cost of dilution, rather than additional private rounds and/or using cashflow+profits to continue the advancement.
As has been said many times, this is not a normal IPO meant to raise funds for a growing company. This is a liquidity/exit event to let investors, founders and employees realize paper gains.
It hard to say they are doing this now because they need the money now - they are committed to spending close to $1T ($1000B) on datacenters/etc, and the IPO will only raise them around $50B (5% of what they need).
The timing seems more decided by the fact that growth may never look better than it does now as tokenmaxxing gives way to customers looking for ROI and cheaper alternatives to frontier LLMs, such as decision models and non-frontier LLMs which are rapidly becoming good enough for many use cases.
I'm pretty sure this is exactly the point maerF0x0 was trying to make without being bland enough to just say it outright.
To your second point, it's been commonly theorized that this is the real reason based on how they have tried so hard to emphasize a specific 6 month period for revenue while it immediately started taking a nose-dive from large companies doing a 180 on tokenmaxxing after that short period.
A nose dive? Really? Do you mean how the growth rate slowed in Q3 to a mere 47% or whatever?
47 percent growth is not fast enough to catch up to their future liabilities. They have to accelerate.
That claim seems surprising to me, since I'm pretty sure their bonds yield less than 47%.
https://en.sedaily.com/world/2026/10/19/anthropic-offers-10-... says, "According to the Financial Times on Thursday, Blackstone was offered a return of more than 10% on subordinated investment in a $60 billion financing designed to secure Google TPUs for Anthropic [...] The double-digit return is a striking concession given that four months ago Anthropic issued about $4.4 billion of debt at 8.5% in a similar deal known as "Project Big Sky."," so we can estimate 10.5%. 8.5% is already well into junk-bond territory.
Can you explain your calculations?
Their current revenue is US$17 billion per year (https://en.wikipedia.org/wiki/Anthropic) out of the US$128 trillion per year world economy (https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nomi...). If Anthropic were to continue to grow at 47% per year, they would reach the size of the entire world economy in 02049.
If Anthropic were to have to pay a double-junk-bond-level 15% yield to borrow the 1 trillion [US?] dollars that HarHarVeryFunny says they need, they'd need US$150 billion per year in revenues to service that debt. At 47% growth per year, they would reach that level around Q3 02031. That seems like a relatively unambitious timeline to build out the envisioned trillion dollars' worth of data centers and incur that debt.
I think this is an overly negative take. The IPO is mostly primary issuance and the cash goes to the company. This extends Anthropic's runway into years rather than months. Crucially, this means revenue growth does not need to reaccelerate and can be allowed to slow to something resembling a healthy technology company.
The IPO has to happen ASAP because financial conditions are deteriorating for Anthropic and private capital has tapped out. They will need cash, they're out of people to get it from, and the cost to get it goes up every day.
I agree the fundamental question of whether Anthropic can grow past its fixed commitments is still a big unanswered question and that there are a lot of fundamental headwinds that you correctly brought up. But at least the IPO takes the business as it exists today seriously.
An IPO can be one of two things and it all depends on who knows what: a way to raise cash to fuel future expansion or a way to offload a lot of the risk onto people who have no knowledge about what is really going on behind the official filings. It could be both but that's unlikely and given that this is Anthropic who are already in my 'untrustworthy' book I am betting on the second. There will be something that they can legitimately claim was 'unforeseen' and then maybe the stock will substantially drop past the lock-up period. Unforeseen could range from 'oh look, our growth stagnated, who could have predicted that?' to 'Oh, look, those models we warned you against are eating our lunch' and many others besides.
This is a bubble, the question is whether it will fill out fast enough not to implode, taking earlier bubbles into account I don't think it will, and if it does it will wreck the economy and then it will still implode, only a bit later.
Sketch me a scenario please where they can grow a couple of orders of magnitude and the rest of the economy survives?
The lore is that Ford created the assembly line and paid his people wages high enough that they could afford the product they were making and effectively jumpstarted a massive upgrade in welfare. This is the exact opposite.
Financial conditions are deteriorating sounds like an embellishment of cash out when you look at the investment plan they have ahead.
Their balance sheets look as good as they will for awhile and they are still the dominate player. So it is the window to IPO. Beyond a couple of years from now who knows. But if they want to IPO now is the time.
The right question is - if you were really on the verge of recursive self improvement, why would you need Wall Street at all?
None of the replies here seem to mention the reasons Anthropic themselves said (not necessarily an endorsement)
- rsi won't happen immediately, and is inherently unpredictable, so they need to bridge the gap
- it makes it easier to trade their shares/ownership with their suppliers. they're fighting over compute allocation like everyone else.
- their "public benefit" plans have always involved trying to share the upside with the public before it goes "exponential"
Isn’t the more parsimonious interpretation that they are not in fact close to RSI?
They don't know that they're close to RSI.
Their CEO claims they are close.
If you thought there's a 60% chance of it happening in the next year, you would anticipate it, and likely talk about it, but also not want to go bankrupt in the other 40% of cases. RSI doesn't mean instant infinite money, either.
feel like that guy has some screws loose in his head
Their CEO could claim aliens are real and that they can fart out money, but that doesn't mean it's in fact true.
...I would like to buy one of your aliens, please.
> their "public benefit" plans have always involved trying to share the upside with the public before it goes "exponential"
LOL. Apparently they haven’t seen the chart put out by their own captured safety org, METR, showing that marginal capability per billion dollars spent is plateauing. There will be no exponential anything.
The METR report said that their rate of improvement has accelerated this year, and that it wasn't from throwing more GPUs at research. There's definitely unknowns here and their R&D spend went up, but note that the benefits of a linear improvement aren't necessarily linear, as you cross thresholds.
If you're worried about competitiveness, note that if R&D costs go up, it can sometimes hurt the mid-tier competitors more than the leaders, as it requires a bigger investment to catch up. Chip fabbing economics became worse in R&D spend and we ended up with (almost) only one firm with the scale. No idea if this will apply to AI though.
I don't know what the technical definition of RSI is, but I think AI needs a good feedback loop for improvement rather than just "thinking" about things in isolation.
I've never seen it solve a problem by "thinking harder", but as soon as I give it access to a feedback loop where it has control it can solve a lot of problems, It sort of feels like brute force, but it's not because it's informed about what it focuses on.
It's the same thing I do, but at machine speed. I had Claude Code help me figure out a sysadmin type problem in about 15-20m one day and I don't think I could have done it on my own in a day.I think the bigger issue is how you convince people to give those findings back to the system. Either you lie about what you're training on or you have to give people a stake in the benefits. For example, I still needed some level of expertise to track down my issue, so why should I publish that so Anthropic can train the next model on it and rent the knowledge back to me?
Repetetive Strain Injury
(SCNR)
I guess you're hinting at the difference between model training (including RLHF etc) and models interacting with code, and improving on that.
I guess the real scenario is "simply" a coding agent pointed at code that integrates collected data, likely with the training code using distributed compute. And distributing the training input improvements is surely also already a solved problem, just maybe not OSS.
I don't see why that's an issue? It doesn't really matter if a very large fraction of knowledge workers aren't convinced. They only need a few of the tens of thousands of people who do your job (often better than you), and your knowledge is available for rent.
They probably won't even need to pay them. They'll just make a useful tool in the domains they're focused on, hand it out to a bunch of freelancers and corporates at a discount, and keep it easy enough to teach the agents knowledge work that simply having better agents is sufficient "stake" for people.
They'll call it something beginning with C - for some reason software engineers trust anything that starts with C. Claude Code, or Copilot, or Codex. Something like that.
Because time and capital matter. If you have a model that is 20% better(say more compute efficient) but also have 50% less compute than a competitor: you lose.
Even if you believe they don't need "Wall Street", having a large number of people owning shares and a stake in the future of the company would be beneficial to Anthropic.
> Even if you believe they don't need "Wall Street", having a large number of people owning shares and a stake in the future of the company would be beneficial to Anthropic.
Ummm... why? This doesn't really make sense. Let's see their current investors:
Google (at least 5%), Amazon (at least 5%), Microsoft, Nvidia, Sequoia Capital, Altimeter Capital, Coatue, Dragoneer, GIC, and ICONIQ.
All of those combined have more economic power (and likely more political power) than most countries in the world.
I’m just so tired of the false altruism of startup culture. This is such a real impactful tool on me professionally and personally that I have never been, I can’t ignore, how disgusted I am. This is the same old playbook, the same old profit taking. It’s a shame.
IMO, this is anthropic conceding they can’t go any further and exiting. Actions always speak louder than words. If RSI was coming, you would be able to secure funding and continue developing independently. There must be nothing evident.
> if you were really on the verge of recursive self improvement, why would you need Wall Street at all?
RSI doesn't mean self improvement for free.
Classic industrial learning curves are, arguably, in the same category as RSI, just with a smaller scaling factor.
> why would you need Wall Street at all?
they still need many billions in compute, while it is not clear if RSI will provide strong revenue gain, so they propose Wall Street to take part in gamble.
because they need an exit for the investors.
They don't. Show me a company in that was founded in the last 10 years and IPO'd after 5.
VC can wait next 5 years. There are 2 options: they need more capital and can't find it in private markets OR investors think their positions are too risk and want to "derisk"
usually they put money for 8 years.
Not the best comp though. Ant / OAI are the fastest growing companies in human history.
They have got to the point where private capital markets are tapped out and only public markets can provide the liquidity that they want/need.
Just as not every monotonically increasing function diverges to infinity, Recursive Self Improvement doesn't necessarily lead to ASI or whatever they're calling it these days. In fact, you could argue the exact opposite: that RSI might actually show how far LLMs really are from AGI/ASI.
> Just as not every monotonically increasing function diverges to infinity, Recursive Self Improvement doesn't necessarily lead to ASI
It is disappointing just how little recognition there is of this point. For some reason, AI maximalists settled on an exponential model of growth in their mind, and I've yet to see one seriously consider whether RSI might not be that. It's a conversation ender, like bringing up an alternative axiom that cannot be debated, rather than a testable hypothesis.
I agree that exponential growth in particular is debatable, but if intelligence doesn't diverge to infinity then it must have an upper bound, which doesn't seem very believable. Intuitively, it should always be possible to add one more processing unit to increase your intelligence (however it is measured) by a fixed amount. So I don't think it can be below linear.
Hey, I appreciate your interest in the conversation!
> Intuitively, it should always be possible to add one more processing unit to increase your intelligence (however it is measured) by a fixed amount.
That's reasonable. The question is how much return you get on your investment, and whether there are "diminishing returns" or "economies of scale" for IQ-per-dollar.
> I agree that exponential growth in particular is debatable, but if intelligence doesn't diverge to infinity then it must have an upper bound, which doesn't seem very believable ... I don't think it can be below linear.
Being able to always increase your intelligence by some amount, at some cost, is compatible with any of "fixed upper bound" (e.g. exponential decay), "sublinear unbounded growth" (e.g. logarithmic), "linear growth," or "superlinear growth" (e.g. exponential growth). Sublinear growth and diminishing returns certainly seem consistent with every self-optimizing system we've seen so far, including agentic AI.
In fact, if RSI is about to happen, you want to stay the hell away from wall street because it will collapse.
Any chance your odds were less than 100%, it would be worth the risk because the hype is there. You set the stage, everyone is on the edge of their seats, then you sell out. Prices will be based on your future performance. Leave the risk with the investors. Maybe you keep some in the back pocket just in case you take over the world
interesting take. makes sense, if they are to achieve AGI, why not keep all this power to themselves?
Maybe they don't want that.
Because you care about letting other people participate in your upside, if for no other reason than that you don't get guillotined
In that case why would any company go public, ever?
probably because even without true, no human in the loop RSI hardware expenditure and power requirements are currently higher than the entire capacity of earth if we did literally nothing other than support AI
Though the truest of true believers also see themselves as one day eliminating scarcity as a concept so it might just be that profit doesn't motivate them.
Because you can get all that cash to do it faster and then you can own the world.
But now wall street owns you
It's either Wall Street, the government, or something else. Public shares are the current easiest way to spread value to the people en masse, more so if you donate shares to the kids like Michael Dell.
Wall Street owns a bit of you, and Wall Street is weirdly open to shares with limited rights.
So we are at the point where RSI is happening, but the idea that RSI leads to exponentially fast growth and SI is based on a number of unproven factors, most importantly that intelligence is scalable significantly beyond human levels. We are also not sure of the limitations of LLMs, how it relates to our own intelligence, and how hard it will be to make the jump to other models.
But when it comes to Anthropic, I am almost certain that it does not make sense to argue based on the typical arguments on maximizing profits. Everything I know about the people working there suggests that they are not primarily motivated by money, but by their mission. I bet they would prefer a lower-strings attached private offering, but have no issue with diluting their own stock, if they think it will serve to move Anthropic further ahead on bringing about aligned AGI. Basically, the diluted money will just be missed donations to EA causes for the most part anyway.
When you have AI models autonomously self-improve, you implicitly lose your understanding of how they work and accordingly your supposed control of them?
AI can be a "tool", but only so long as you understand how it works and what the implications of its use are. Being an enormously powerful tool implies, the consequences of not understanding and not knowing are proportionally enormous as well.
Currently, LLMs are used practically exclusively by "professionals" who, more or less, know what they're doing. The idea of applying them "everywhere" completely misses the gap in understanding and responsibility for the vast majority.
Anthropic believe they are building a god with RSI, not a tool. That was never their goal
I've often heard skeptics say AI enthusiasts think they are building a god but I've never seen any evidence. Are there any quotes implying Anthropic think they are building a god?
> I've often heard skeptics say AI enthusiasts think they are building a god but I've never seen any evidence. Are there any quotes implying Anthropic think they are building a god?
Not Anthropic specifically, but there's this thing that I recently read:
https://www.nytimes.com/2026/11/09/opinion/ai-anthropic-doom...:
> A.I. company leaders often talk about how their work might lead to human extinction soon. This is astonishing. Even if you wanted to destroy humanity, you wouldn’t say so. If, however, you wanted to save the human species, wouldn’t you stop developing this technology?
> There is an explanation for why some tech leaders, so seemingly worried about an extinction-level event, are plunging ahead with A.I. development: Mankind’s survival, while important to many of them, is less critical than building something they believe to be not only conscious but godlike. A substantial portion of the A.I. community, in celebrating this belief, is quick to support any action or statement that reinforces the idea that the technology is like a deity. They might call for regulation, but only in specific ways — perhaps by deploying more A.I. to control A.I. — that adore the technology’s powers. It is that adoration that is nonnegotiable.
It's by the guy who apparently invented VR and was apparently mentored by Marvin Minsky. So he likely has the kind of access that gives his opinions credibility.
(Archive link: https://archive.is/SSgkC)
Thanks, although that still sounds a bit like a skeptical viewpoint.
> Thanks, although that still sounds a bit like a skeptical viewpoint.
I think it's unlikely that an AI enthusiasts would literally claim "they are building a god," but such an attitude (or something very similar) is implied by their statements and attitudes, e.g.
1. Talk/hope of building something that so exceeds human capability, it's beyond human comprehension and control.
2. Taking existential risks for humanity (by their own statements) to try to get there, against all reason.
3. etc.
I guess. Anthropic's about page is more "We aim to build frontier AI systems that are reliable, interpretable, and steerable".
I guess they think AI will become smarter than people but I'm not sure that's a god. I've always thought of gods as the dictionary "a supreme being, creator, or a supernatural entity" rather than a souped up chess computer.
> I guess. Anthropic's about page is more "We aim to build frontier AI systems that are reliable, interpretable, and steerable".
That's a marketing page. It sounds like their view is more like "we're building a god, but only we can be trusted to make a good god instead of a devil."
https://www.nytimes.com/2026/11/05/technology/dario-amodei-a...:
> These schools of thought fused for Dr. Amodei into an unyielding conviction that A.I. could be so dangerous that only he and like-minded technologists could be entrusted with building it. That catalyzed his stated efforts to create A.I. before people without concerns about the safety of humanity did, and spurred a desire to control the technology, his friends and colleagues said.
> I guess they think AI will become smarter than people but I'm not sure that's a god. I've always thought of gods as the dictionary "a supreme being, creator, or a supernatural entity" rather than a souped up chess computer.
We'll seeing God as "a supreme being, creator" is only a particular conception of god. IIRC, polytheists often gods as just powerful supernatural entities that are owed deference (because otherwise they might cause you trouble).
> or a supernatural entity" rather than a souped up chess computer
Obviously a AI machine god would fail a "being supernatural" test, but I'm sure the thinking goes that a super-intelligent AI would be so powerful, it's natural-ness wouldn't matter
All they did was build a really good software engineering tool, and that’s gonna be when the bubble pops, when you realize you really can’t commit it to handling any real workflows, and the slop that people are creating, vibe coding, that have never touched code in their lives.
nice handle, my doot
what do you think an AI "that can wipe out all of humanity" is exactly? are you expecting by god we mean some old man with white beard?
Sounds more like a rival species. We wiped out the Dodos but I don't think that makes us gods.
from the dodo's perspective it does
Nice analogy. We know what the end result of people worshiping false gods is.
Can you give an example of people who worshiped a false god and of what happened to them? Because I am honestly at a loss. I am not even sure what a false god is and what the difference is with a true one.
Do we?
If you're looking at history for an answer, the end result is somewhere between total destruction and something approaching world domination.
So, not that informative, really.
Don't you have one already? What improvement would that artificial one be and to whom?
Anthropic desribes itself as a "public benefit corporation" in its IPO. The irony. Or is it sarcasm?
A god isn't your subordinate. You cannot "program" your wishes into it, like a genie/jinn. They (or their investors) want to make themselves into gods. Over you.
> Currently, LLMs are used practically exclusively by "professionals" who, more or less, know what they're doing
Actually, most LLM usage right now comes from vibe coders who don't even read the code, much less know what it does.
The domains where they apply it, privately for instance, aren't of immediate import. Their fuck-ups stay local.
The consequences of "AI use" are manifold and very poorly understood. That doesn't make them less impactful, on the contrary.
Whether you look at "humanoid robots" or incorporeal LLMs, when they are more capable than yourself, you become their dependent counterpart, not their "master".
A car, plane or train can travel long distances much faster than I can. I'm dependent on them for that task.
Does that mean I'm not in control of when and what I use them for?
Source? AFAIU most of Anthropic's revenue comes from enterprise usage, who presumably have an incentive not to generate pure, unvalidated slop
https://www.tradingkey.com/analysis/stocks/us-stocks/2623001...
> When you have AI models autonomously self-improve, you implicitly lose your understanding of how they work and accordingly your supposed control of them?
This was always the case with ML, even absent RSI. Big bag of weights is a pain to figure out exactly why it can do whatever it is that it does, leading to all kinds of blind spots about how they go wrong.
> Currently, LLMs are used practically exclusively by "professionals" who, more or less, know what they're doing.
Even the people who made them don't really know what they're doing, hence https://www.felonybench.com
I think that this is a great article on all of this: https://substack.com/home/post/p-224216856
He distinguishes between weak recursion (using sotfware to build more software), and strong recursion (handing over model development to AI which does everything), and makes a pretty strong case for the fact that only weak recursion is happening.
This maps to my experience with AI models, they reduce the cost of experimentation massively, but they can't (currently) design experiments themselves.
Even then, training RL is very data hungry, and most profitable tasks don't have good data so even if we got superintelligence (whatever that means), it's entirely possible that progress would still be bottlenecked by lack of high quality training data.
Thats a great distinction.
The hope was that weak recursion could produce strong recursion by automating the iteration of ML pipelines.
Theres also the idea of LLMs producing synthetic data to contribute to new models. Perhaps that is not as effective as hoped.
> Theres also the idea of LLMs producing synthetic data to contribute to new models. Perhaps that is not as effective as hoped.
Wasn't model collapse/model decay a big issue since the beginning? i know that RL kinda mitigate the effect, but if this was close to not be an issue anymore, wouldn't we have a paper on that already? All that i've seen on the subject was about mitigation, never about solving the issue.
Sorry if my question is dumb, I need to do some research about the difference between image generator and text generator, i feel like my understanding of LLM is skewed by my usage and understanding of Z-turbo, but i only have that much time in my week.
> the idea of LLMs producing synthetic data to contribute to new models
This never made sense to me. Seems analogous to inbreeding in biological organisms.
It works because artificial neural nets take a lot of examples of something to learn it (way more than natural neural nets). So at the simplest level it's just copying items in the training data enough that they become salient.
More complex synthetic data generates things that could be in the training data but aren't for some reason. For example, machine translation training corpuses often contain a lot of formal language (because formal documents are the ones that get translated), so you might generate a bunch of casual conversation to improve the translation model's ability to handle that.
>So we are at the point where RSI is happening
do you mean ppl using claude to improve claude?
> Everything I know about the people working there suggests that they are not primarily motivated by money, but by their mission.
And what is that mission?
I'd almost prefer it if they were motivated by money, then at least we know what we're in for. All this 'mission' stuff seems to effectively amount to 'we're saving the planet, sorry you got in our way'.
> are not primarily motivated by money, but by their mission
Bring about ww3?
Are we really entertaining that 2010’s “it’s about the mission to make the world a better place, not the money” dross again? You can see this nonsense parodied in literally the first episode of Silicon Valley
Jokes on them, I've had RSI since 2017...
sniffles
Apple, Amazon, Intel, Google, NVIDIA and Tesla all had world-changing product before their IPOs but they didn't stay private until clear market dominance.
Because private rounds still dilute you.
And VCs tap out well before $100B.
And they'll need more than $100B to accelerate widespread economic diffusion.
And RSI can't hallucinate gigawatt power plants and TSMC fabs into existence.
Sure but currently the market wisdom is that companies tend to stay private longer and longer: https://www.nasdaq.com/articles/why-do-companies-stay-privat...
This is no longer the days of Apple, Amazon, Intel, Google, NVIDIA and Tesla.
Anthropic stayed private extremely long, if you look at their market cap.
Startup market cap is a fantasy until a week after IPO. It’s just a multiplier of money in
Well all market cap is "just" a multiplier of latest trade.
> Apple, Amazon, Intel, and NVIDIA didn't stay private until clear market dominance either.
Apple, Amazon, Intel, and NVIDIA all went public in an entirely different world, before the JOBS act.
I'm not necessarily taking the same position as the person you are replying to, but using these companies' IPOs as comparisons for what Anthropic is doing is not exactly Apples to Apples as it were.
Why not? Win the stock market, break ECC and own the internet. There are many ways to make infinite money if you have infinite intelligence but not infrastructure. True RSI wouldn't announce itself
wtf was tesla's world-changing product? when does it come out?
The first mass produced (or just viable) EV. It changed the world to make EVs realistic and now we have loads of other (better/cheaper?) options.
That's some wild alternate timeline take.
Even if that were true (i.e. the models were good enough for infinite recursive self-improvement), the risk is still rapidly increasing with time. I presume most VC's would rather take the current exit with their pants intact.
Commoditization is coming and faster than they had expected. That's why the push to IPO now. Delay another six months and their $1.3T IPO could be half that.
Kind of hard to believe in recursive self improvement, every time I tried setting an LLM to loop on itself to "recursively" improve code towards a goal it always descends into utter garbage. I think the main challenge is probably knowing exactly what you want to get, and then having a training landscape that is smooth enough so you can climb there? I guess these models can probably iterate their architecture to max out existing benchmarks but at some point they will essentially just do p-hacking as the model that improves the model will invariably leak the validation data into the training process on the meta level, or so I would assume. And if your goal is to create a model that can compete with human intelligence in math then how would you even come up with a scoring function for that, will you let the model do multiple years of fundamental math research and then see if it produces something that is novel and interesting? And how do you score if it's like 99 % there, 50 % or 10 %? From my naive understanding that's probably the main challenge, these models can only optimize if you have a clear measurement of goal achievement that can be climbed to, if there's only a very far fetced goal without clear intermediate success states I don't see how the current generation of models should get there.
Same experience.
I was excited when I got a good metric system implemented because that meant concrete signals for Codex to use for optimization.
It attempted ~5 things. All of them did not improve performance past the baseline.
How much more for the unclear goals, general ML research, etc. My takeaway from all this: You need domain expertise to drive the models.
> ...every time I tried setting an LLM to loop on itself to "recursively" improve code towards a goal it always descends into utter garbage.
I've had this just today with both Fable 5.2 and Astra. It was an extremely simple task too, basically just "Here's the extremely detailed ticket (a large ticket, but extremely well documented, one of those tickets where even an intern new to the team could just follow along and get it done in a reasonable timeframe despite the size), here's the MR, let's make sure that we trim some of the fat in this MR from all the iterations we did on this ticket over the last month it's been in review". Both models shat themselves monumentally, started changing random crap all over the place, and in the end this exercise in removing some code only ended up adding a LOT more useless code that was doing fucking nothing, not to mention how unreadable and low quality it all was.
Time and time again, my actual real-world experiences with this tooling is a "meh" at its very best. We have all the harnesses and MCPs and all the other bullshit the AI bros like to shove on you, good CLI tooling, sandboxed environments, basically unlimited access to SotA models, excellent human-written documentation for the context, a mature, stable and battle-tested CI environment which makes changes extremely easy to test. Anything other than the most simple possible translation tasks, and none of these tools ever actually save any time whatsoever.
Every fucking time it's just introducing 3 billion useless unit tests that assert x == x despite who knows how many instructions in the "harness" detailing in excruciating detail how to write tests. Or it's introducing incomprehensible garbage comments that leave you more confused than if there weren't a comment to begin with, or the infinite other plethora of rancid bullshit this tooling leaves behind
[flagged]
[dead]
They need the money to have a chance of getting to RSI, and $100B is hard for private rounds to realistically supply. An IPO also lets VCs show real returns to their LPs instead of paper markups. This then helps VCs raise larger funds for later investments
What is RSI?
Recursive self improvement, basically a concept in which models improve themselves on their own, iteration after iteration.
Thing from sci-fi
Recursive Self-Improvement.
Or Repetitive Strain Injury. If LLMs acheive RSI then programmers won't have to type as much, so the risks of RSI will decrease.
Excellent take. Anthropic will take on RSI so we developers won't have to.
A huge number of people who are decision makers for the IPO will become multi millionaires or billionaires when it happens
These people are incentivised to do it ASAP to mitigate the risk of any kind of crash or scandal or whatever putting their insane wealth at risk
Basically, if you could snap your fingers and make $50M today, or have a 99% chance of making $200M in 5 years time, which would you choose?
Log expectation says to pick 99% of 200M. You should bring it down to 73%. This doesn't account for what you could get with 50M in the 5 years span though. I have no good model of that.
"Market dominance" isn't the right metric. VC's want maximum price at the moment of lockup expiration. With so much uncertainty, it's smart to eye the exit and have the option to take gains.
They have made no claims that the internal models are yet good enough to say that RSI has truly kicked off.
All insider and outsider predictions seem to think "true RSI" will really begin in 2027 or 2028.
> It strikes me that if their models were good enough for recursive self improvement
I just can't imagine this is true when their overreach problem (doing more than you ask), hallucination problem (lying), redefinition problem (doing something completely orthogonal to what you asked), and harm problem (doing something that is exactly the opposite of what you asked) are all far too high at this point, and by most measures - all of the recent models are worse on most (or all) of these metrics.
They are giving up here in RLHF to benchmaxx the metrics people are looking at to pretend like they're making huge gains, when they're largely running in circles.
They are getting better at pass@1 at the expense of far worse p90s on real agentic tasks.
> For some reason they need the $100B today at the cost of dilution...
You can do the math on the dilution, which will be on the order of ~10%, give or take. If the new shares are worth more than existing shareholders paid for theirs, each share can be worth more even though the percentage is smaller.
Couldn't the additional liquidity and funding provided in an IPO make the difference of who gets to RSI first? If there's only one winner, being a close second while staying undiluted might still be a worse outcome.
It makes zero sense. Even if the model can self-improve it doesn't mean the hardware need will go to zero immediately. Human society as a whole is a self-improving system (at least in terms of technology) and it doesn't mean humans consume less and less resources.
They need resources and $100B can buy them that. I don't think you need a conspiracy theory to explain that.
The whole idea of self-improving machine equals immediate singularity is just wrong and ridiculous. I don't know why so many people are attached to this idea. Perhaps just because "singularity" is such a cool sci-fi word?
It wouldn't be immediate. But most models of RSI conclude to a singularity a few years later max.
Chip fabs take many years to build, and that can't be accelerated with intelligence alone. Much of it is limited by physics and practicality, such as having to do the steps in sequence. You can't "align" the ASML machines until the foundation concrete has set!
Yeah, but given a medium that leverages nitrogen vacancy centers for phonon propagation, you can replace photolithography with ... I dunno, but maybe the God-in-a-box does.
"Recursive self improvement" is not new. Compilers have enabled recursive self improvement since the 1960s. Semi-supervised leaning is not new either.
When people talk about recursive self improvement, they mean autonomous self improvement.
No humans in the loop.
What semi-supervised learning tells us is that any system with no humans in the loop will at some point reach a limit, and require more supervised data.
Deep learning had no humans in the loop, but there's always a bigger outer loop with a human somewhere.
And, the explicit goal of these companies is to break that bigger outer loop. That's the reason for the investment, and the reason for the valuation.
You can place bets that these companies will be failures if you want.
thats cause none of these systems are Intelligent yet?
They all knew about the stuff that is coming out now (Jensen stepping down due to chinese spy stuff) and has been out and debated for a while now (circular financing) and money drying up as a result. Winter is coming...
Comment from a perma bear. So take it with a grain of salt. lol
Yeah they’re completely stumped. They stole the idea for LLMs from other people and have now hit the limit of that idea. They’re spending a billion on payroll and none of their people have a clue what they are doing.
This is their (investors) exit strategy. I don't $100B private funding at the current pace.
Without this IPO they'll need to either stop the bleeding or coax yet another multi-billion funds (which most of them are already balls deep in AI)
fund or bust
I think they are feeling the breath of open weights models from China on their necks.
recent NVDA events are actually bullish for ANT, as GPUs wont be as easily available to chinese proxy data centers in southeast Asia as they were.
2nd bullish thing seems to be that chinese labs are having difficulty in distilling latest frontier models. No deepseek pro for some time now!?
also government, defence, financial and similar institutions and companies will almost sure never use chinese open weights models.
similarly, other nations including the US's staunch allies will never use closed models for government and defence, so that doesn't mean anything.
Employees need to get rich before they become too important to not be government controlled?
If they get RSI they need even more money for compute.
I don't think recursive self improvement will lead to a sudden takeoff. It initially probably won't be much better than human assisted improvement that's going on now and still constrained by compute available.
Once you have a super-intelligent system, of course you want to scale it up. Remember, Amodei's goal is "countries of geniuses" in data centers. Super-intelligence can't just think those data centers into existence.
This seems like a reach. Just because Anthropic could theoretically become a future infinite money printer, that doesn’t stop it from needing money in the interim.
It also doesn’t stop investors from being happy liquidating at an already good return, especially since they can choose to liquidate partially.
Simplest possible answer is A: they are dramatically ahead right now, and B: there is not nearly that much privately held money available for relatively risky investments.
Based on METR's evaluations of their unreleased models, they don't seem to be dramatically ahead. Actually, it seems that each iteration brings smaller performance gains than the previous ones.
EDIT: Maybe before downvoting read the actual evaluations?
https://pbs.twimg.com/media/HWYbAX9b0AA-SWt?format=jpg&name=...
So the same as the last two AI fads. Error rate being halved by each generation results in smaller and smaller increments.
Lmfao, it takes some real balls to post a chart showing their performance growth over the last year is speeding up and conclude it's bad.
The gains between generations are smaller because model releases occur more frequently (this is primarily driven by them taking more frequent snapshots of the base model during training).
The title of your chart is literally: "As of October 2026, benchmark scores appear to be increasing at 1.9x their pre-October 2025 rate [95% CI 1.5x-2.8x] - when including recent internal models."
[dead]
And once all those engineers cash out, China will become dramatically ahead because they are only a month behind already and can pay way better than the IPO
So much of "dramatically ahead" is due to the Claude Code harness being better than anyone else's.
Fable is great, certainly, but it's no better at writing or reviewing code than the top-end Carbon or Astra models. To the extent Anthropic has a moat, it's Claude Code. Obviously that's not much of a moat, but their competitors seem content to camp on the other side of the drawbridge for some reason.
What makes it a moat? How did you compare? I don't think CC has particularly outstanding integration (used in practice) or performance. People use it because Anthropic shoves it down their throats, making it risky to use anything else with their subscriptions, and generally gatekeeps their models like crazy.
I use all three major harnesses regularly (Antigravity, Codex, and CC) and CC is better. It gets used for writing code, while the others are used only for reviewing what Claude writes.
Codex is pretty close in a lot of ways, as the other poster says, but Astra consumes tokens at a higher rate, and when it compacts it completely lobotomizes itself. That used to be a problem in Claude Code as well, but it has been largely solved (although at the cost of making the compaction take much longer.)
Antigravity reminds me of the old comic strip where Firefox and Chrome are duking it out, while Internet Explorer is sitting in the corner wearing a helmet and eating out of a jar of paste.
I don't see in your reply that you attempted to decouple models from harnesses, it seems you're mixing them up. I regularly test different harnesses on different models and for my use cases CC is just about as performant as OMP with Claude, for example, but it takes a lot more tokens. I don't see anything special about the harness itself, that's why I'm asking about actual comparisons.
I don't see in your reply that you attempted to decouple models from harnesses, it seems you're mixing them up.
Normally I run the models that the harness is intended to support. You can't run Claude models anywhere else besides Anthropic's own CLI and desktop harnesses -- or at least you're not supposed to -- without paying out the nose for API tokens.
I do use DeepSeek 4.1 Flash 1017 in Claude Code when I want an abliterated model for security-related work or unhobbled browser control, though. I know it's possible to get OpenAI models working in CC, but I haven't bothered. Gemini I'm not sure about.
I use a 3P harness, and Claude performs significantly better than any of the other models
Open source ones like OpenChamber, etc are doing good work in competing on this front (including being able to use your subscription credits directly)
I mean, OpenAI has codex? I find it pretty equivalent. So they are trying to equalize. (Less said about Google CLI attempts the better). And there’s definitely not model equality - Astra was a big step forward but generally loses on daily utility to opus 5.5, much less fable. I would be very scared for Anthropic if it was trying to compete purely on harness; I suspect most of its usage is by default because the models are better. In the pre 5.5 phase I saw a lot of migration to codex/pi, and I’d be fine without CC as a harness today.
Exit liquidity? I feel like it would be a lot easier to raise $100b from a few private investors if you had reason to be confident that you were gonna make a self-improving cash printer. If, however, you weren't sure what you were gonna actually be able to pull off and saw a plateau or drop coming you could use an IPO to generate hype and get some liquid cash and then dump your position on retail and institutional investors if it doesn't work out. Why don't they don't rely on private investment and profits? I don't have the information to verify this for sure but one theory is that they don't think there will be much more private investment or cash flow.
I mean there's only so much money you can raise from private equity. It's entirely possible they've achieved some big breakthrough but need more money to distribute it than private equity can supply. That said I'm not sure they need another breakthrough to justify the stock price, just gradual improvement and user growth
Lets say you knew that RSI would need 10x the current available compute. They can't continue raising from VCs at that scale to fund the buildout.
If you need 10x the available compute you’re not going to get it for 10x what you already paid. You’re talking about potentially destroying all of your vendors.
If you’ve ever don’t consulting work, you know how dangerous it is when the majority of your revenue comes from a single customer. You stop being independent, you stop having your own set of values, and if anything happens to that company, you’ve already proven you lack the ability to court as large a contract from other customers.
It always ends in a loss of identity and huge layoffs.
Making vendors product triple their current production rate for the next five years isn’t even possible to start this year, because they have to build facilities and train employees. Nobody runs businesses at 50% capacity anymore. That’s considered wasteful, even stealing profits from your shareholders.
They can’t even get memory chip companies on board with their koolaid.
[dead]
> For some reason they need the $100B today at the cost of dilution, rather than additional private rounds and/or using cashflow+profits to continue the advancement.
Both Anthropic and OpenAI seem to be burning cash as if it was a game of startup chicken. Of course they all desperately need cash.
There is a lot of value from LLMs but it is something that I can switch easily. Yes, some frontier models are much better but users can still chose to use cheaper models for most of the work. In fact most applications, through which people will interact with LLMs anyway, will not need frontier models unless they offer "chat with AI". Anything that solves specific problems (even multiple problems) does not need frontier LLMs.
Anthropic and OpenAI will have to become more of the end user application stack. Files, calendars, emails, photos, and much more have to pass through them for them to keep making money. Else they cannot make money like the way they have been in this early era of LLMs.
Switching models is easy as a solo developer. Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc. I think Anthropic will look a lot more like a cloud provider like AWS or GCP. Same-looking product, very high switching cost that would have to be driven at the CIO-level because of all the integrations that have to be redone, IP concerns etc. And ultimately they are selling compute capacity.
Edit: I should clarify that I don’t think this justifies their valuation. It puts them in competition with much more entrenched players with established customer bases, and who aren’t in massive debt to provide their compute. I’d also like to distinguish between a model provider as someone who provides weights vs a model provider who connects their GPUs and models to your codebase and internal systems - I think the latter is where the sustainable business is.
Incidentally this is why I still feel Google is well-positioned in the long-term AI race. If they can remove their head from their ahh and make a coherent product offering across Workspace, GCP and Gemini, they could become as entrenched as MS.
I would assume AWS is probably the most interested in acquiring Anthropic out of the three major cloud providers.
>once all your employees have it integrated with GitHub, their IDE, etc.
Yeah but already existing things like Github Enterprise copilot and openrouter kind of kill that lock in before its even started, no?
> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc
I don't think this is entirely true. Companies are deploying open-source LLM gateways to be able to do that very easily now. Today, you can switch Claude CLI to any model besides Anthropic via https://github.com/BerriAI/litellm and there are major companies doing that.
This works with your favourite ADEs such as Orca as well so I disagree with this premise. The whole experience of switching is pretty seemless based on personal experience.
We saw this play out in the cloud era, notably with OpenStack. Even through the core abstractions (chat for LLMs, compute and storage for clouds) can be almost perfectly abstracted over, providers will race to add niche, enterprise-y features that are harder and harder to put behind a gateway or proxy. Those features aren't the core value of the platform but they are important enough to create lock in.
When I write a system against a particular cloud storage API, I end up implicitly depending on a bunch of deterministic subtleties of exactly how this storage API works.
AI is already so non-deterministic and fuzzy, I'm not sure the same issues apply.
And if the LLMs are as powerful as the very same providers claim it will be trivial to write code/configurations that bypass lock in.
Agreed, deploying AI gateways has become extremely common in enterprise settings. A lot of admins think they are going to use it for guardrails, but I think the real value is in centralized cost tracking and ability to (relatively) seamlessly aggregate providers.
AI can program a cost tracker tool pretty easily.
We have like a dozen different LLM tools available to us and it's as easy as clicking on a dropdown to switch in every single one of them, and we have several thousand employees. Self-hosting with the cheaper OSS models is also becoming more and more attractive for larger orgs.
That's just inference. Claude.ai is a platform that enterprise IT teams connect up to all kinds of other applications, and gets use beyond the claude code CLI. Non-developers get used to this functionality - whether it's their form-building stuff, artifacts, slides/presentations, etc... they're building an offering far beyond just inference. I agree the latter is a commodity now, though companies will compete on privacy options (ZDR, guaranteed confidentiality, etc)
Many large enterprises don't use Claude.ai. All their traffic goes through an internal gateway that routes to Bedrock. In addition, there is a whole ecosystem of LLM related infrastructure/tools deployed by "enterprise IT teams" where Anthropic barely has any presence.
But many do, so price them according to that. This is like saying "my office doesn't use Microsoft". Sure, lots don't. Lots do, no one is questioning that Microsoft has a very viable long-term market there.
Except that claude does not nearly have a dominant position with enterprises like Microsoft does.
For infra sure, but its dominance in other areas is quickly eroding. My org is super heavy Microsoft/Azure and we have all of their tools. Everyone making anything useful is using Claude + Databricks because it is a better experience for both builders and users by every measure and it isn't even a remotely close competition. Power BI and Copilot are a total wasteland. The only Microsoft program with any staying power is Excel.
Similar at my $(dayjob) and can confirm.
> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc
Once the cost reaches a threshold, everything is doable. We ditched Datadog in less than a month. Someone I know had their company ditch slack in a quarter and google cloud usage of 100+ million in two. Everything is doable.
It probably took years to get there. Furthermore, it sounds like an anomaly.
I think when something becomes a management-level item in an org, like AI, it is a hard thing to switch unless it becomes a management-level problem.
Most of the orgs are responsible for this and will do whatever it takes politically or not, to justify the decision unless management overturns it.
> It probably took years to get there
I already mentioned the timelines. Cost is a beautiful line item in your balance sheet that can get things done pretty quickly, especially when it’s as big as AI. It took less than 2 quarters for us to go from “hey use ai in everything or get fired” to “hey we’re putting in default limits that are intentionally very low, if you need more, you’re going to need approvals”.
The stickiness of AI as a whole, let alone a specific provider is not that high as people are making it out to be.
Working for a 10k+ corporate and we made it pretty easy to switch to any provider, people here can use Anthropic's, OpenAI's, and our own self-hosted open weight models very easily. It's one drop-down or `/` command away to switch between them.
I think other companies are probably doing the same, the moat of a AWS/GCP/Azure is much deeper with how contrived it is to migrate between them even if you abstract as much as possible with something like Kubernetes.
Interesting, I don’t think that’s incredibly common but that’s certainly not good news for them. And also not great for OpenRouter.
Vendor lock in is quite well understood, most larger companies (the one's I have worked with anyway) are aware of the risk and take steps to actively avoid it. Once bitten, twice shy.
Openrouter is really meant for individual developers and startups.
Openrouter was acquired by stripe, I'm sure they're not worried.
Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc.
Speaking as someone who has been at professionally this since the 1980s, I suggest that while sometimes switching costs and network effects happen "organically," in this century businesses devote enormous amounts of attention to artificially building switching costs.
It's such a dirty practice that we have a four-letter word for it, a "moat." But of course, the moat isn't really to keep competitors out of a market, it's actually to keep customers trapped within it.
I fully expect every one of these AI providers to put as much work into trying to trap their customers within their ecosystem that they do to improve their capabilities.
LLMs make it easier to bypass the moat, too. They can automate migrations, etc. pretty smoothly.
(Since we're talking about moats and cyber-feudalism, where does siege warfare come in?)
Since siege warfare is about bringing down the fortifications and a moat is part of those fortifications, cyber siege may be something akin to patent trolling or IP copyrights? Fire off dozens or hundreds of claims against your target and drown them in legal costs.
they haven't really done that so far. no offense but LLMs didn't exist in the 80. or 90. or 6y ago. and I'm just as old as you.
Then you have the experience to know that every land grab in technology so far has followed the same enshittification path: At first it's all about competing with other entrants to provide value and win customers. Then, inexorably, it shifts from winning customers to defending their turf. Then, inexorably, it shifts from protecting turf to maximizing extraction from their turf.
If you believe that this will be different, why not? But for now, I'm expecting this to go the same way. Yes, LLMs are something completely new. But also, the people behind them are exactly the same as the people behind every previous land grab.
I can't wait for anthropics next big drop to be that it can order you a pizza, steering towards benign, token burning features that you didn't ask for and eye real-estate abuse for ads.
It's the end of an era. Lets pray open weight models give us a real choice soon.
In the meantime, Stonks up Anthropic. I'll always remember the good old days when you championed developers and changed what was possible.
> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc.
I'm not so sure about this. I guess it depends on how well people did their job there.
Ideally, whatever people built is loosely coupled to that third-party resource, meaning that switching cost will stay low.
After all, it's probably just prompts + an API layer. Unless one micro-optimizes their prompts for claude (which then breaks once a new checkpoint drops, hence is a bad idea regardless), pointing them towards a different API endpoint should be doable.
Currently we are building agentic systems for various business functions like Legal and Finance. How these models perform in those tasks is paramount, and things like cost per run is only a part of the equation. It can become very subjective, and things like brand recognition comes into play. The cost of a counsel or a VP finance overshadows the savings you get by micro-optimizing for a cheaper model. We tend to use the best-in-breed LLM for the various tasks - mainly Claude and Gemini, and sometimes GPT.
> How these models perform in those tasks is paramount,
Then you have no choice but to use your own hosted model because that's the only way you can be sure the model isn't going to be removed or quantized/nerfed behind your back.
If your system can widstand the fluctuations of closed models over time, then it can most likely support switching between multiple providers in the first place.
I should be more clear. The "performance" I'm talking about is not entirely objective in these use-cases, and the bigger part is something you can't reliably measure through tests or evals. The value proposition of the frontier labs is their post-training taste, how reliably the model handles ambiguity and infers intent, while at the same time progressing at the leading edge. Self-hosting trades that for output stability, and absorbing minor drift within one provider is still far easier than switching labs when your workflow and UX are tuned around a specific model's quirks.
> The value proposition of the frontier labs is their post-training taste, how reliably the model handles ambiguity and infers intent,
That's also literally what frontier labs break all the time, be it by removing the model outright (remember the outrage over the forced replacement of GPT4o with GPT5) or by tampering with some configuration (aggressive quantization or whatever bullshit occurs right before new models are released).
ahhh, that explains it. you're optimising for the "trust me bro" metrics
If you ever need to scale to millions of customers, then cost per task is paramount. If it’s a one-off vibe coded custom project for one client, then best-in-breed is mandatory without it falling apart.
Ur case actually strength the argument for open weight self hosted model. You would have precision control over not only the technical issues, but also the legal issues.
Once the open weight models are good and cheap enough, there is no reason not to use them
Spending money in the most effective places is smart... and then there are the stupid businesses.
> I guess it depends on how well people did their job there.
Given that the goal of the whole project is outsourcing the work, what are you expecting here?
I think you'd be surprised. I've seen orgs entirely switch fundamental tech choices to save 10%.
Once they realise that you can use Deepseek / GLM for 10% of the cost these labs are done.
Exactly, model itself is commodity, and integration is also not a moat because AI can code integrations with a prompt.
My company switched from direct access with providers to AWS Bedrock. Now we just pick which model we want from the list exposed by Bedrock. We can also leverage tools like T3 which allow hand off from one model to another.
Are you using AWS AI-DLC?
It's trivial to switch. The company I work for has 1k employees has already switched like 3 times in the last two years.
Are they really switching when so many docs, diagrams and info is stored inside Claude Design, Whiteboard and meetings?
We store those things in confluence, figma, and zoom. MCP allows the LLMs to work directly in those systems as needed.
They aren’t noobs like you, who uses frigging Claude as their storage platform? Ever heard of connectors?
Problems that don't happen if you make everyone use claude code, as they should.
This is the era for boomers to get over their fear of the command line.
Claude code can be used from the Claude app without ever touching a command line
It's nerfed
Easy to say, not so easy to actually get your mechanics, your project managers, and your business operations staff to get over that hurdle unless you’re willing to handhold them through the process of changing directories or explaining what an environment variable is to them. (This isn’t just boomers btw. Lots of young people have had the command line abstracted away from them their entire working lives)
That’s why some companies will lose competitiveness because basic AI literacy isn’t taught.
There are many perfectly successful companies out there with limited computer literacy among much of their employees, let alone AI literacy. Those companies are great targets for Anthropic’s enterprise sales team, if they can provide an intuitive user interface that allows said employees to make use of AI tools, allowing them to leapfrog the need for computer skills.
We’re not talking about developers, we’re talking about people who just want the technology to let them do their job. What even is AI literacy? 2 years ago it was prompt engineering
Weird take. Tech boomers started with tape or commandline. The ide only became the development environment of choice in the late 90s, firmly with genx and millennials.
Claude code is a terminal interface not a command line tool. More like vim than sed.
Visual BASIC was 1991. QuickBASIC, Borland Turbo Pascal, SmallTalk-80, NeXT InterfaceBuilder, all pre-1990, several well-pre-1990. Boomers absolutely had, and indeed devised, the IDE.
Given his name he probably means German boomers. The country whose chancellor called the internet "Neuland" (uncharted territory) in 2013.
Model switching behavior is going to be far more complicated.
First, everyone and their mom is selling AI now. It is being bundled in nearly every product. Buy CRM to run your company - they will upsell you their bespoke AI - mostly RAG/chatbot using the data inside the platform. This is an important area because today lot of companies are trying to build their own AI bespoke workflows. But companies like SAP, Oracle will spend money on improving this aspect. And people who buy/use AI for this purpose don't care if the underlying AI is Claude or not.
Then there are cloud providers. You can get Claude, OpenAI from AWS Bedrock etc. They will take the heavy lifting of changing integrations, IP concerns etc to keep people on their platform. With time expect them to make it even easier, not harder to switch models. Also, they will push for open source models because it will be more profitable.
Lastly buying from direct providers. This is here the lock in comes in. But I believe fewer and fewer enterprise will buy directly - many preferring to buy against their cloud commitments.
My F500 company switched ~10k employees of Claude to copilot in 30 days. Google did similar between Jetstream and Claude. The moat just isn’t there right now
Copilot lets you use Claude models though.
And Google models and OpenAI models. The point stands that this looks like a race to the bottom.
| Switching LLM providers as a company is not
I really think you overestimate the level of lock in here. If a companies tells the devs to use X because it cost 1/10 of the price they will just have to suck it up and switch.
I didn't particular want to work on a "all in agentic project" but that the nature of being employed.
The same LLM we use day to day will make it trivial to switch out providers in our infrastructure.
One thing that makes easier to switch with LLMs as opposed to other tech is the text-in text-out nature of the LLMs. All specs and data are in text files mostly in natural language which is patent free. This makes it harder to lock in content.
As you have written, the agentic harness is a slightly different matter with plugins and features. But the core tech makes replicating software a lot easier so you can in principle use an agent to make it easier to switch from its own harness. There are caveats to this since in practice the quality and feature sets of harnesses are not the same. But in my opinion, it is far easier to switch agents than switching other tech that came before them that used proprietary formats and apis to lock you in.
> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc. I think Anthropic will look a lot more like a cloud provider like AWS or GCP.
This might be true today because Anthropic/OpenAI/Google have good sales AEs, but as soon as company's start doing FinOps on their LLM spend, the game is over for them. The model will become fungible and hot-swappable (as it already is) and it'll be a race to the bottom.
With some gateway inbetween managing the model responses, MCP and skills (see https://modelcontextprotocol.io/seps/2640-skills-extension) this becomes very easy
I think the future will be a lot different they we expect, AI is going to be the infrastructure layer while there will be toolings for each processes, so switching between model is a built-in feature, i.e. the tools will inject specific prompt or context based on the models, and all these are designed by people selling the tools, hence, a moat?
VS code or other ides with multiple providers makes it pretty easy.
Also for larger companies like Amazon the danger is they replace Anthropic completely with self-hosted models.
Let's say that the face for largest foundation model slows down enough to make the companies cloud-like, instead of whatever they are mow. Imagine the free credits that OpenAI would consider giving you as long as they are spent on migration out of Anthropic. They could even classify conversations by themselves.
This is the logic behind B2B SaaS's revenue multiples, and yet AI itself is causing those multiples to rerate based on a change in expectations about the durability of an entrenched SaaS provider.
Given how unreliable these models still are and how fast everything changes i suspect switching is not that painful even for larger orgs
Integrations with Github and IDE are nothing. It's like changing your email software.
When was the last time your company changed email provider?
They said email software and not email provider. Changing email providers is hard. Changing email software, not so much.
I think the /s was silent
Depending on how the company leverages them, it's super easy.
For us it's as easy as clicking a dropdown. The copilot vs code extension allows for this ez pz, the same is true for companies that implement an AI gateway for other tooling.
This is why you recommend tools like OpenCode or OpenClaw that commoditize that layer.
I am really surprised that companies who are worried about AI spend don't try that route.
Totally agree with your Google thesis. I would never count them out. I say that as someone that uses Claude (and a little chatgpt), but not Google's AI at the moment.
With ad money Google never had to learn how to ship a product that makes money. An obvious place they fail is that when something breaks there's no one to talk to to fix it.
Switching LLM providers as a company is even easier than a solo developer, most large companies I know are using AWS Bedrock and selecting another model is basically just a checkbox for them
As far as I know, our corporate has deals with all of them: Anthropic, OpenAI and GitHub Copilot.
They stroke a great discount deal with all, so different teams/departments have different provider, and those using Copilot are even free to switch between models as they please (although with lower usage limits).
You could make the argument that it's not worth switching SAAS providers for enterprises when the costs were like 10 dollars a month per developer and switchign would require 1 team to work for half a year... but with AI providers it's more like paying 1000 dollars a month per developer vs paying 200 dollars if you strike a good deal with different provider and swtiching costs are more like 4 to 8 hours of work for each developer.
I guess what I’m saying is that means AWS is their provider then
Indeed, and I think AWS is in a perfect position to consolidate the entreprise market rather than Anthropic here, they already have the rest of the server stack so this is just another addition.
Or LiteLLM and switching providers is just super easy.
Thanks for using us !
nah it's pretty easy.
it's easier than changing okta
it's easier than changing google docs and even Gmail
it's easier than migrating cloud
etc.
and we're talking several magnitudes easier too!
What?
Have you used Copilot at a company?
I can literally change my model in 3 seconds.
The moat is as shallow as it gets. Investing in a single LLM provider at the moment would be a mistake.
I've observed that there are some companies and some folks that are very fanatical about a specific provider. "Only Claude" is very common. "Only GPT" less common, but still see it.
A lot of the non-technical and semi-technical folks are only comfortable using a specific client like the Claude desktop app. A lot of teams wrote skills and eval'd/benchmarked their skills specific to a model family and harness.
The "I can use any model, any harness" or "I only use a meta harness" (Orca, Paseo, Herdr, etc.) crew is relatively small IRL. Most people are still single-session, single platform user mode.
Most orgs have an enterprise contract with a single provider so all of their internal assets are built for the provider. It goes beyond skills, but also the telemetry, enterprise policies, and managed configuration.
For a company though, the idea that a few disgruntled employees will shift massive purchasing decisions is a bit of a stretch.
We have a developer on our team that keeps asking for a claude code enterprise license, we keep telling them "no, it's way too expensive, get used to using the copilot extension/cli".
For consumers, sure, but the bulk of the revenue opportunity is enterprise. Anthropic/OpenAI have a hard row to hoe IMO.
Is it just that they want the harness? Or your Copilot config has disabled Anthropic models?
It may still be possible to use the CC harness with the Copilot sub.
> Most orgs have an enterprise contract with a single provider
Yes, either Google Gemini or MS Copilot. Both come as part of their Office suite licenses.
As an only-clauder, there's another elephant in the room. Anthropic is by no means perfect, but:
* using OpenAI supports the Altman/Thiel/Musk/Ellison/Karp/Trump billionaire Orwellian worldview and also ads
* using Grok supports a ketamine-addled open fascist sympathizer jizz-spewing 12-year-old-edginess memelord and his similarly broken worldview
* Google's models are pretty good but every single product they have ever had is ultimately either suborned or killed by the advertising division
* local models pretty much only half-exist because Jensen Huang wanted to cheat on his wife; future is unclear
One can argue for harnesses and so forth being lock-in, but the ultimate lock-in is morality and wanting to have a civilization at the end of all of this; I can't recommend either enough
And Anthropic is perhaps some kind of FTX part II, a cartoon villain attempt at world domination. Dario promises to cure all disease!
for us (200+ people) switching was a single prompt
Actually LLMs themselves make changing LLM provider or harness a non-issue, in my experience.
A gateway like GoModel can make switching transparent, along with the many other benefits you get with a gateway.
It’s literally a menu in Copilot.
The model is just some REST endpoint you switch out even in a lot of enterprise setups.
It’s weird that people don’t seem to get this. LLMs are the most easily switched-out technology I’ve ever used as an engineer. The input is literally just free-form text.
> It’s weird that people don’t seem to get this. LLMs are the most easily switched-out technology I’ve ever used as an engineer. The input is literally just free-form text.
It depends, if you're automating business processes (honestly probably where the money is), then you'll need a really comprehensive set of evals and moniotoring to ensure stuff doesn't break if/when you change providers.
If you have none of that, then switching will be very expensive (but it was ever thus).
> you'll need a really comprehensive set of evals and moniotoring to ensure stuff doesn't break if/when you change providers
Unless your self-hosting open weight models, you need this even if you don't change providers, since you have no control of what's on the other side of the API.
That just means the business automation is not deterministic, and highlights the issue with LLMs. The solution is not to switch providers but instead make the LLMs generate something that is deterministic given the same input.
> That just means the business automation is not deterministic, and highlights the issue with LLMs. The solution is not to switch providers but instead make the LLMs generate something that is deterministic given the same input.
I'm thinking of stuff that would typically be outsourced (like compliance stuff for identity verification et al), where it's really really hard to have deterministic rules.
LLMs are definitely a step up in dealing with fuzzy inputs, and enables you to mostly automate stuff that really wasn't feasible before.
But you do need really good evals and monitoring to make this work effectively.
Ah that would make sense then. I was thinking strictly in terms of business logic for handling input of data from an external source; sort of glorified data validation and then a decision based on the input data.
You'd be crazy to spend LLM money on that, but its probably happening all over the place.
Yeah, it's the absolutely weirdest thing about all of this. People keep telling me I need to up my AI game yet no matter how advanced the tools get I'm still typing stuff into a text box. My skill is typing English. I was already pretty good at that.
If only there was a tool that could automate the switch/transition from one LLM to another...
People seem very unimaginative about the ways in which somebody equipped with a lot of intelligence and compute, and control over both, might make money.
The recent Anthropic push into biomedical research gives a clue.
Additionally, I think people are being unimaginative about what future generations of frontier models might be able to do, and the business value of having a 6 month head start on competitors.
For example, people are now content with small models for agentic coding, but even frontier models were mediocre at agentic coding just 12 months ago! Frontier adopters have had more time to transition their systems and processes to what we're already taking for granted.
I am not unimaginative about Dario's megalomania. I just don't believe he has the ability to execute. He has no prior experience to Anthropic and nothing he has done as CEO would create confidence that he is actually capable of operating at this scale.
Except for, of course, currently operating at "this scale"?
There have been less likely FAANG-ish founder-CEOs than a 45?yo, ex-OpenAI founding member, Princeton biophysics PhD.
Exactly. Ambitions are obviously a bit more than accessing emails and calendar.
We also see that enterprise revenue is more important than end users when we compare Anthropic's financials to OpenAI.
This is equally true for how risky it is to build such a business on top of a 3rd party black box. Model nerfing is widely speculated and the only true way to guarantee that the models you're using are stable and consistent is to run your own hardware. Not to mention the recent Navier-Stokes controversy.
The moment you find a money-making formula on top of someone else's black box model, there's nothing stopping them from taking it for themselves.
Models being nerfed is widely speculated primarily by people whose first instinct after suboptimal results is blaming the tool.
It is not something that has affected productivity in any measurable way.
Concerns of AI labs illegally accessing your usage data to steal your business model are a similarly imagined problem.
Personally I make my business decisions based on real results, which are imo significantly better with the latest SOTA models.
Model nerfing is rampant from people using subsidized plans.
Stories are much fewer and further between for people using the API. Which makes sense, the subsidized plans are "You get what we give" whereas the API is "You get what you pay for".
This is the same argument we have heard many times with SaaS that would presumably get replaced by open source equivalents. In practice it does not happen because there is a lot of value in having someone else deal with a problem.
SaaS have vendor lock-in, they have your data hostage and whar importantly your habits: other software never gonna be 100% the same.
Changing LLM backend on other hand takes 2 seconds.
And it's not all or nothing: you can just keep anthropic $20 plan for planning and do 99% code generation with chinese model.
You're focusing too much on the technical lock-in. They are providing:
- A stable and reliable platform you can build your prod on
- "Unlimited" capacity (something impossible today with the amount of GPUs available outside of labs)
- ZDR that is trusted by companies vs a random provider on OpenRouter
- Central governance
- E2E integration in their CLIs/Web clients/Desktop Client/etc...
> ZDR that is trusted by companies
Nobody trusts Anthropic's ZDR, in the limited cases where they even offer it. The key thing is that weight activation sequences from a query are not "customer data" they are internal Anthropic data. So in Anthropic's legal theory they are training on their own internal data, not "customer data," and that is perfectly legal, even though it is the exact same thing in practice as training directly on customer data.
> Nobody trusts Anthropic's ZDR
Very clearly false. You might not, but most company are going to see Anthropic as more trustable than a random provider on OpenRouter.
> random provider on OpenRouter
obviously that is not the bar. but microsoft and amazon are much more trusted than anthropic. with anthropic it is just assumed that they will steal your data.
> A stable and reliable platform you can build your prod on
Your talking about Anthropic right?
They have likely had the scale their infra faster than anyone on the planet before. I'd say they are doing fine ;)
That "someone else" is just shifting from a single open source maintainer to an LLM.
The problem here is having a stable access to LLMs with strong trust the provider will respect ZDR, won't poison the models and will provide a stable platform you can depend on.
a big move into end-user software would mean that they have to compete heavily with their own largest customers. The economics of offering SaaS are also under meaningful pressure and don't warrant anywhere near the valuation that is being suggested
The biggest moat with applications like MS Office is compatibility. Sharing a slide deck or spreadsheet with others is a simple decision, you know they have it or have software that can read/write it.
I don't get the need to have Anthropic build their custom versions of MS Office apps, I can tell Claude to generate a word doc from a wiki page and it does a pretty damn good job. Anthropic's statistical median level of software that they had Claude create isn't going to replace Office apps to the point where companies cancel/stop renewing their MS Office subscriptions/licenses.
The other element is trust. Do end users trust their data in Anthropic's systems? A lot of people get creeped out when they search for content from one device in their household and then nearly instantaneously they start seeing ads from other devices on the same topic. How creepy will AI get if it starts consuming all your docs, spreadsheets, personal finance info, emails, etc.?
I beg to differ I already am stopping using MS office recently but that's mainly because I really dislike how they lock up the apps if your late on your annual payment. It's a grating value capture model. I'm sure I will have to get back to it at some point but in the meantime google is providing great optionality and I don't have a concern that the software stack has glaring security concerns.
On the trust thing - I don't trust anthropic and I don't think MS has been a great steward over the years either.
The moat of backwards compatibility and plugins is why MS Office has survived decades of competitors without any appreciable loss of market share.
It's hard to see Anthropic replacing it, and even if so - why bother, the revenue is miniscule. They need 100 MS Offices for the compute contracts to pencil out.
End-user software is going to be under a lot of pressure. If you're Microsoft, Apple, or Google: you can easily copy products or integrate ideas into their platform. I see companies like Adobe, Salesforce, and Oracle having to downsize significantly to stay profitable. Having said that, my in-laws still pay for an AOL email so I don't think their cashflow is going to zero soon.
Adobe seems to be in a tough spot, because so much of the lock-in is client side, I think Salesforce is fairly well protected, it's just so impossibly difficult to remove once a company has fully adopted it. Similar to the staying power of the ERPs of Oracle and SAP.
It's the same really. There have always been alternatives that can work with Adobe's various file formats. Even more aren't going to change much, at least for their enterprise key customers. This is not only the case for Adobe, but many others as well, e.g. MS office is still a thing these days, and so are things like 3Ds Max or Maya, albeit having many compatible cheaper or even free alternatives. It's not so much about features, pricing or even stability. It's about customer support. Do I want to ask an LLM and test my luck or write a GitHub issue and cross my fingers that someone will read it within the next weeks? No, I will pick up my phone or write a mail and get a response within hours if not minutes.
I ask my llm to write custom software and love the freedom to customize it to my needs. Today I do a presentation on Ubuntu with a new "Presenter" app that works offline, runs 100% in CUDA on GPU and streams videos, starts in 2 seconds, lets me demo live robotics policies in 3D simulations and Opus 5.5 wrote it yesterday. This may sound very unusual, but I think it will be common in the future: moats disappear one by one.
With no feedback loop and reasonable token use?
I would say that Apple's Create Studio can move toward feature parity faster with Adobe. My point if you're not a platform provider it's going to be harder to make a profit.
The risk for Adobe isn’t that we replace their software with some AI generated alternative. It’s that we bypass that class of software altogether and have an AI do the work.
"There have always been alternatives that can work with Adobe's various file formats. "
And yet me and quite some others still yearn for a flash alternative. There never was one.
Interesting point that challenges the limits of LLMs!
Any of us could vibe code flash now. How to coordinate it as a dev ecosystem of designers and users?
Does it make sense for everyone to JITVibe presentation apps like the person above? Maybe we'll evolve to branding.
"Any of us could vibe code flash now. "
Surely not just prompting like this and it will one shot it. The usefulness of the flash authoring tool, was it was battle tested and polished.
But I did gave it a shot to took up developement again of abandoned www.wickeditor.com (a web reimplementation of flash). Good results, but limited time and energy for that right now.
The big problem is Photoshop. I have no love for Adobe, I proudly moved my department off of all Adobe products a few years ago. I am a big fan of open source solutions and I am always impressed at what the GIMP team (and some others) have accomplished.
But…
Photoshop is king. Everything else is behind by a solid decade. If you’re a professional the $40 a month or whatever it is now means nothing to you as well. It has the professionals are all on it, and because the price isn’t astronomical, that’s what everyone else uses who needs to use that kind of program more than once in a blue moon.
Premier? Replaceable. Lightroom? Pretty replaceable though still somewhat ahead. Photoshop? There’s only one Photoshop. And as much as I’m loathe to give Adobe any credit, it’s the best by a mile. There are too many essential features in QoL things that other programs are missing.
Luckily my department doesn’t need it, but if we did, we would simply have to accept Photoshop.
> If you’re a professional the $40 a month or whatever it is now means nothing to you as well.
Exactly this, but also for an employer, paying $40/month/user is good value in order to ensure you have a room full of productive designers or image editors.
No employer is going to dump Photoshop and force the designers to re-learn everything they've learnt over years or decades. There would be such an enormous loss of productivity.
If you've ever watched a designer at work you would see that. They just breeze through Photoshop, hundreds of things in a few minutes. Super productive. All thanks to muscle memory, knowing all those shortcuts, knowing blindfolded where all the toolbar buttons are, knowing how the filters behave, knowing where everything is in the dialog boxes.
A similar comparison is all those "just write it in Rust" people. Well, sure. But if I've spent decades coding C or whatever, I'm not exactly going to be able to switch to Rust overnight am I .... realistically its going to take a timeframe measured in years to reach the same level of coding proficiency. And no, vibing with an LLM is not the same thing.
Also Photoshop has native integration with Adobe Indesign and Illustrator, so there's also the cross-tool aspect too.
I'm not sufficiently skilled with Photoshop to gauge how well this replaces it, but you may be interested in this supposed clean-room reimplementation of Photoshop: https://github.com/storytold/photocraft
Heard about this! Haven’t had a chance to check it out yet. I’m sure once I have an actual project that needs me to roll up my sleeves with Photoshop I’ll give it a shot. I probably should have mentioned it in my original comment as a possible option
Not a graphic designer, so, truly asking out of curiosity: what are the QoL things and essential features in Photoshop? I've been slumming it with GIMP for years now and not felt anything very obviously missing, but again I'm not a pro.
Compatibility issues, which can be a huge deal partially due to near-vendor lock in. If you historically been on Photoshop, bringing your working/former projects into another software is not easy, which matters because revisiting work is common.
Not all tools are non-destructive in GIMP. Things like raw support, smart objects, retouching, etc. all either are super thin compared to Photoshop or require workarounds/a lot of manual effort. There are just lots of tools you expect in Photoshop that either don’t exist or exist in an inferior form. I can’t elaborate too much because I don’t really touch Photoshop much these days, but I work with people who do and worked in production long enough to know the expectations. GIMP is great but Adobe is a massive company with deep pockets, it’s hard to keep up. Their user experience is miserable but the tool itself is just far more robust, and a client simply isn’t going to accept that you won’t do something that Photoshop could do quickly because your alternate program can’t do it or does it with a lot more effort. That’s the reason I ultimately dropped Final Cut!
AI is pretty amazing for migrating. source: I'm using Claude to replace a large Tableau ecosystem. What would have taken years is now taking months.
I'm not sure corporate procurement has ever selected the cheapest and best option, so I think they may be fine. Plenty of reasons to avoid completely locking into your cloud provider as well.
> If you're Microsoft, Apple, or Google: you can easily copy products or integrate ideas into their platform
This argument doesn't hold water. Google tried like no one else to have a chat app and it failed miserably more than a handful of times. Same for social networks.
Sorry, I was referring to "end-user software" which in my mind is something that people pay for directly.
Like Discord?
Adobe creative suite is $70/m. From most businesses perspective it's not something worth looking for cheaper alternatives and the alternatives has existed for a long time now.
now imagine that said customer/competitors have been uploading/generating their source code, problem reports, marketing collateral, and other IP _to the LLM company_ for the last few years.
I have tried so many times to get off Chat GPT. But it just... knows me? Switching to another LLM seems like a huge loss. For coding projects especially... I've set MD files to the max, explaining how i like code to be written, etc. etc. i've tried to tell it not to create a bunch of files and such, but i can never use an IDE. I feel like i'm the only caveman coding in a chat window... but it still seems the best to me? The only time it's been worth it for me to use an IDE LLM like codex or cursour is when i'm prototyping a website, but then i just go and pay someone to implement it in wordpress because it's so much easier to maintain that way.
Why haven't people switched then? Same could be said about Google search, Facebook, X etc. Claude is the de-facto SWE model now, yes you could use an open model but you would always be wondering if Claude would do better, like using Duck Duck or some other Search engine
> Claude is the de-facto SWE model now, yes you could use an open model but you would always be wondering if Claude would do better,
In my testing (incredibly similar workflows, moving around between claude code and cursor), I haven't found that much difference between Sonnet and GLM-5.3/flash.
Sonnet seems lazier, but has better prompt adherence, and is constantly telling me it can't do things, while GLM will just Find A Way to do whatever I've asked for.
I really appreciate being able to see GLM's thinking tokens, as I can head it off quicker. Claude's a little harder to steer, but the integration in Claude code makes it much easier to leave it running on things overnight, which is hard to get working properly in Cursor.
Overall, I'm not sure Anthropic have that much of a moat, in coding particularly. This seems weird to me, as they have so much more usage data that's hard to replicate.
> like using Duck Duck or some other Search engine
The difference between Anthropic's models and alternatives is not as big as Google Search vs other search engines
Google search is shit these days, depending on what you are trying to find.
Yes, they know that. That’s why Claude is becoming a platform like Google Workspace.
They need to leverage Claude Code in the software industry to position themselves as the go-to platform for businesses.
Meanwhile, Google and Microsoft, which already dominate that area, seem to be dormant.
If Google and Microsoft have gone dormant in this space, I have to think it’s because they haven’t been seeing any ROI, either. Possibly because customers have been so underwhelmed.
I’ve been using Office Copilot more or less since it was released, and the general opinion around the office is that it’s a huge waste of time. The auto-transcripts produce 3 pages of fluff when previously someone would send 3 sentences’ worth of what actually mattered. The auto-drafted documents rarely add anything meaningful beyond what was already in the prompt. The question answering and research tools are only as good as Sharepoint/Confluence/Jira/etc’s pre-existing search feature, and therefore untrustworthy, etc.
What made Anthropic exciting was they had locked onto a use case that reliably generates positive value: coding. Not much else has proven, from a business perspective, to be anything more than an exceptionally buzzworthy money pit.
I have been using Claude privately for coding a few weeks now, and my company encouraged us to use company paid Copilot recently. I tried coding with it and the result made me irate i had to close it it was so infuriating. The idea that i need to point out it’s bugs and have Copilot tell me “you are absolutely right!” Haha never again
Yes, that's the direction I've been witnessing for Claude too. But it's a short to middle-term strategy IMO, by the time companies are ready to drop all these apps they will need something else entirely, not Claude's slides or spreadsheets or Salesforce.
The fact that Frontier AI can become Google Workspace at a flip of a switch is what is crazy valuable. Anthropic and OpenAI can enter and disrupt any market, especially software, faster than any company ever could, because users want the flow to start and end in their chat interfaces.
I think eventually almost all non-creative software will, essentially, be a wrapper around a session.
This pattern has already happened before, in the translation industry. Someone figured out how to learn from and recall context from ordinary translation work (the "translation memory"). It started as an add-on to Microsoft Word, and matured into a standalone software, that was ultimately a wrapper around a document editor. Then language management systems plugged into that wrapper, hey presto, every translator at your company does the same work they were always doing, and you've produced an entire corpus of quality translations to reuse everywhere.
Now _translate_ that idea over. Every time any human works with an agent on anything, simple heuristics find everything true and reusable, save it to the everything-memory as skills, refences, glossaries.
Anyone does any work, all agents can now that work at that organisation. Self-fine-tuning models everywhere, and it fits into corporate intellectual property expectations.
I have done something like this at a medium-sized listed business.
Helping my wife this past week try and setup an automation in her workspace account revealed how dormant google is here.
Gemini is unable to take an attachment from gmail, read it, then place it in the correct drive folder and update a spreadsheet with what it found in the attachment.
For whatever reason, Google decided to firewall "Gmail Gemini" from "Drive Gemini". Gmail Gemini can send files to drive, but not edit anything, and Drive Gmail can edit files, but cannot be initiated from gmail.
Meanwhile claude code with Google extensions can do this no problem.
Google, wtf are you doing?
> Meanwhile, Google and Microsoft, which already dominate that area, seem to be dormant.
Google owns 15% of Anthropic I think.
And Google offers Argon 4 to paying Workspace and Google One customers now. How's what was the number 1 model on nearly every single bench a few weeks ago being "dormant"?
I know people all in in the Google ecosystem (getting credits from Android phones they buy etc.) who only swear by the Google models and who are now using Argon 4: I asked them and a few days ago they had access (but they were already using other Google models before that).
Doesn't GMail have billions account by now?
I'd tend to say with billions of users on GMail and a model like Argon and 15% of the Anthropic shares, Google is not where you think it is.
It's easier to use claude to do stuff insider workspace than it is to use the integrated gemini. Claude has more power to do stuff than gemini, in it's own house. That is such an egregious fumble that it's honestly hilarious.
It's almost like the workspace devs are anthropic plants that are purposely underminig google.
The sad thing is Google could totally own this space. They had a huge head start, more raw data (from search) than anyone, a huge installed base on Workspace and consumer Gmail, tons of compute resources...
Integrated gemini stuff sucks but it's nothing that special about Claude, general agentic tools are just better than app-specific ones. Agy is also much better at doing things in workspace than the bespoke in-app gemini stuff
Which is true, but if you are going for the enterprise market, you need to have the thing that is right in front of the user be the thing that works.
Right, because Google actually has assets and a responsibility to keep their customers secure, whereas Claude can do things that are completely insane from a security perspective because they have no liability.
[dead]
One thing I have noticed; as a project matures frontier AI is less useful essential.
Qwen3.8 and Meta Muse Glimmer are great at "fill in the middle" of frontier architectures and plans. Frontier generated plenty of great context already to keep them on rails.
Delegating like a CEO down a pipeline of expensive experts to cheaper local small models could become a common trope, especially if Apple M7 and beyond live up to rumors as LLM tuned, and chip competition exists to keep forward progress, SaaS models are cooked.
The goal for chip corps too is the right mix of generic model enabling logic; not necessarily a full concrete model but enough of the abstract to efficiently boot strap and run a model; move common patterns to silicon not data.
Token vending is little more than behaving as a "wrapper app" over electricity. There is zero technical moat to their business.
True. We will end up getting more Google alternatives. Nothing beyond that for now at least.
> There is a lot of value from LLMs
Asking sincerely... apart from FOMO subscription revenue, what is the actual money-making proposition?
I don't know why nobody has said this yet, but...
The eventual logical move is that they build a completely reinvented AI-native operating system.
The funding they're getting gives them the resources to build and compete on a fundamental level, IMHO.
If you don't believe me, look at the recent demo where they had Fable 5.2 build an OS from scratch.
They are coming for the whole stack, my opinion.
Why? Given that there is a limit of things that they can do, why would inventing a new "AI-native OS" be an interesting target? They could instead focus on solving actual existing problems in science and engineering, finding solutions to problems that they know people already care about and would pay money for, instead of putting a lot of effort into maybe inventing a middle layer, that might be used to solve problems or maybe not.
There will also be a lot of competition in that space, because everyone can take a stab at building an "AI OS" (whatever that means) using AI for basically free.
One more piece - say Google Gemini gets way better than OpenAI or Anthropics offering, or Microsoft Copilot etc gets way better...
If Microsoft or Google's AI is killing it, and it's built into the OS, how will Anthropic or OpenAI compete unless we run into the same old antitrust/competition issues with OS?
At that point, they might just say - "fine, it's easier to just have our big AI brains and money make a new OS we control and we can compete too."
Again, why bother why IT? Just do the things that IT is built to help build. Solve medicine, energy and materials directly, instead of competing at AI integration.
I see your point. You're proposing they can just do an end run around the "business and world problems" directly.
I guess that could be a thing, but, that puts them in competition with the people who they might want to be their customers, whereas I don't necessarily know that they would see other tech companies as customers unless they were super interested in partnerships.
According to "the normal progression of companies" though, you might be right because after a company has becoming big enough and exhausts consuming its own market, it often expands into verticals - we've seen that with traditional big 5 consulting companies or IBM, where they expanded into "working embedded with their customers on their problems directly" many years ago, and now every company in the industry approaches it that way.
That is corporate partnership and field work, not so much consuming the other person's work/business... whereas I could see them just consuming the OS because "it's no big deal when you can do everything you need with AI".
But I take your point.
Sure, a few thoughts as to why:
- at some point, look at what they have they can do to grow to satisfy shareholders - AI companies have been acquiring companies that make developer tools - that is the build side - but once they've exhausted that, if they want to keep growing, what do they go after? Bigger and better models at ad infinitum? I don't think they can go on like that forever, and, if optimization of AI and competition keeps cutting into their main business line of LLMs etc, they have to diversify.
- If everyone has the power to make apps, there is only so far you can go there - my guess is that the pressures to reinvent regular things like office suites, email clients, calendars to be integrated into their desktop tooling is part of this
- who is in the best position to be the platform/front door for everything, if everything depends on AI?
- when have these kinds of companies ever said "this boundary is enough"? It never happens, they keep going, keep trying to find ways to expand, capture, build moats, etc.
- look at what their desktop apps are turning into - they are already an application layer and becoming moreso every day, at some point they will ask - why are we sitting on these other OSes... we have enough money and we can get into more "hard" engineering things, like building hardware using their own tech (which they are already experimenting with), and if you're building the hardware, why not build the OS?
- and, what is an OS in the future? Have you considered what a post-AI OS even looks like? Does it need a start menu? Does it need any of the legacy stuff? Is it a local software factory?
There is someone already experimenting in this space - the guy who founded Basecamp and is building Omarchy [1] Linux... he sees it.. how long until these companies do?
If they don't build this, what will Microsoft do? Both Microsoft and Apple are well down their way, Apple is probably further ahead, but neither of them are the frontier model companies. Don't forget Google has a stake in OS too.
"Everybody will try to build an AI OS", but which ones are the most likely to survive in our current economic system?
If our economic system was based on partnership, I might agree there isn't much point in these companies building OSes, but ours is based on competition and domination generally... so unless the AI bubble truly does pop and the funding stops (which it may of course), how else do they keep fueling their stock prices to dominate the market?
I think something is going to have to give somewhere in the chain... otherwise the ease with which any software can be replaced will be too high and I suspect they will be forced to compete.
One last thought - between Microsoft/Apple or Anthropic/OpenAI - long term - who is in a better position? The debate arises from that question, in my opinion.
[1] https://omarchy.org/
How would they make money from an operating system?
I hate to even put this out there, but "OS-as-a-subscription" (OAAS) could be a way. Your Claude payment covers all the software running 'your' computer, plus the ability to develop new 'apps' for specific needs on the fly telling the OAAS computer in human language what you need. Throw in services like email and cloud storage and some customers might find such a bundle attractive for the right price. It would suck revenue away from MS, Apple, Google. Enough to justify this valuation? No idea.
vertical integration
Based on how shoddy their customer facing applications are, I wouldn't trust any of these AI companies for an OS. It's like Google II - can't trust them to support a product longer than it took to develop it.
I agree with you on quality... but if AI/LLM/etc continues down the path of continual improvement, it's only a matter of time until the products become better or different enough that it isn't an issue.
And making products fast and first over quality has never stopped these companies from trying, when they have so much funding....
I do not share your same hope of improvement given time. The commitment should be on quality first, not speed of development. This is why we are all drowning in a proliferation of poopy modern software.
The fact that their desktop offerings are so pap is an indictment of their engineering prowess and a demonstration of their apparent inability to use their own (actually very good!) LLMs to generate decent software.
It baffles me how a technology so good at spewing out software is apparently unused by the people who are developing the technology.
Fair enough. It will be interesting to see if the world returns to sanity and focuses on proper engineering discipline, planning, quality etc...
I've lived through enough hype cycles in tech myself that I do know that eventually it tones back down and people go back to work, perhaps altered from what they did before with new approaches, but back to work nonetheless.
I just felt myself that this particular technology, and this particular cycle, might be a little different - let alone in how it caused changed in our society whether it worked or not, but that also, there is still room to go.
I'd be fascinated to know what they say on the inside, if there is still room to go and to improve, or if we're nearer some sort of plateau in progress.
> They are coming for the whole stack, my opinion.
Sucks to be them then, the best chance we have to keep this thing under control is not have the same supplier give you the whole stack.
Hard agree with you here.
It feels like people are still trying to bet on the horse that will achieve gAI.
I'm fascinated by exactly how an investment in the company that first reaches AGI (or whatever we decide to call it) might pay off... It feels like the stocks would absolutely be worth owning in the immediate term because they'd be hot property at the point where people realise it's happening.
The thing that I'm less clear on is, if and when they achieve some kind of recursive improvement exponential growth thingy, isn't that going to heavily disrupt the entire economy / stock market? In that environment, would Anthropic's stocks really be a good bet, given they have to operate within the economy?
> The thing that I'm less clear on is, if and when they achieve some kind of recursive improvement exponential growth thingy, isn't that going to heavily disrupt the entire economy / stock market? In that environment, would Anthropic's stocks really be a good bet, given they have to operate within the economy?
That's a long-term problem to be dealt with later, greed dictates to pursue the former as long as the music is playing and everyone is dancing. Similar to 2007-2008 when it was clear that things were breaking but the incentives were to play the game for as long as possible before it imploded.
It's clearer to me why this works for generic investors than for the AI companies themselves - unless their plan is just for key employees to cash out and live on a private moon just before Consequences arrive.
>> that first reaches AGI (or whatever we decide to call it) might pay off
It is a myth. They are chasing science fiction. They either dream of an omniscient overseer who will take control of society and nominate its shareholders-parents into the governing elite, or they envision a chatbot that will solve every problem, again turning shareholders into the power brokers. They forget that nobody will ever be allowed to "win capitalism" and take over the planet. Companies have are torn down for far far less. Every AI model is data, ones and zeros. It therefore can be copied/shared/leaked. Intellectual Property law is not a ladder for assent to lordship. It can and will be rewritten or outright ignored rather than allow capitalism to collapse.
“Yes, the planet got destroyed, but for a beautiful moment in time we created a lot of value for shareholders.”
> It feels like people are still trying to bet on the horse that will achieve gAI.
I think that at this point gAI is just a marketing blurb, and the actual race is to dominate current practical applications involving basic RAG and ReAct loops. This can go from anything between software development, business intelligence, and market research. A company whose top brass can use a team of agents to do what nowadays they assign to mid- and top-level management is an executive with tighter control over the whole business process. For this you don't need gAI.
I've noticed they've actually stopped harping on about this AGI nonsense, I suppose because no one was buying it to begin with and they themselves didn't really have any idea wtf they were talking about when talking about "AGI". Now it's all about a bajillion agents running autonomously or whatever
No no, Anthropic just published an article claiming "jagged AGI," another marketing term. In it the writer spells out why they haven't achieved AGI though. But the marketing is still going strong, now with even more vague terms!
The frontier is addictive.
> Yes, some frontier models are much better but users can still chose to use cheaper models for most of the work. In fact most applications, through which people will interact with LLMs anyway, will not need frontier models unless they offer "chat with AI"
I am finding some really routine tasks to be borderline with frontier models. Performing E2E testing of enterprise web apps would clearly disintegrate with local models. You need that reasoning black box on top. I don't care what your favorite benchmark says. I care about what actually fucking works.
The people who don't understand the economic situation are those who are in the pure play space with AI and multi agent circuses. Why bother spending any money when the occasional failure has literally no consequences? Who in their right mind would pre-pay for tokens?! I wish I could see the statistics on what % of HN uses AI for fun vs for work. It is clearly a kind of Factorio entertainment experience for a lot of people. If I was just using it for entertainment this whole IPO business would look really silly to me too.
We all love moats, but I mean, it is still possible to make money in an industry simply by being the best at what you do and charging for it.
Anthropic has shown a consistent ability to deliver the best general purpose models. Can that continue indefinitely? Will models become "good enough"? Will open weight models catch up to SOTA models? Will some genius start a new company with better models?
And, on Anthropic's side, will they be able to use their market power that comes from being the best to push through regulations that will create a moat; instituting some sort of mandatory safety checks that coincidentally are exactly what Claude is trained to pass, regulating the amount of compute or trying to claw back data centers to prevent new training, etc.
Or maybe they just have the magic sauce and they're going to stay on top of the game and people (like me) will be happy to continue paying money for their product.
Easily in the context of the corporate world is to pay for something, that something gets installed and then just works, and if it doesn’t work there’s always someone you can call 24/7 to come and fix it. I don’t see how this is possible with open models.
the answer is to use a gateway that all the prompts go through. There are many proprietary and open source solutions for this. You get the benefit of making it trivial to switch between proprietary providers in case you are unhappy with the performance or squeezed on price. The AI Gateways put cap on LLM providers' margin upside.
Additionally, the gateway allows for caching, additional security checks, centralized monitoring. I think most corporations have a multi-provider setup anyway.
Anthropic has basically no support.
What do you mean? We use Bedrock at our company and I can switch to literally any model, including the open ones, by just typing /model and picking it, even including inside Claude Code. It's ridiculously easy to switch, and imho GLM 5.3 is good enough for 99% of my daily tasks already.
You pay a service provider, who manages the open models… there is absolutely nothing special about it. The hardware can be something you own. Or you rent. Or you just pay the service provider to access the open model apis. Lots of options here, it’s not different from pretty much any other software service in the corporate world
Isn't that exactly how Linux companies are making money?
Good luck in calling Anthropic support...
i use llm for
- work: I need frontier, cost of mistake is huge - home: i do entire renovation with it, cost of mistake is big. monitor baby health, development, etc: cost of mistake is big , taxes: cost of mistake is big casual researches about certain facts, shopping, booking: cost of mistake is medium
non of this fits : i will run an expensive laptop hidden from the baby, since i'm on the move, there is a small percent of casual queries that normally will go into finish products: google ai, muse, etc.
100% - brace yourselves for enshittificarion.
I’ll always remember the good times.
But you’re wrong ser about small or cheaper models. Choosing to work or not having a choice to work with cheaper models means you work slower and more methodically because you have to plan out the work and size it to fit. This has huge implications on the value of the work you can produce as an employee or solo developer, and it’s a skill working with these SOTA models - there is specific crafting that must be done to be effective with each and their capabilities.
You will see the old eyeball real estate game, forcing more of your experience into their apps and platform so you can see ads or “new slop features”. You will see the SOTA models more closely guarded in an effort to bait you into that platform, and yes, you will see them doing things they never should be doing, moving towards an open AI like model where it can order a pizza, where monetization it was always important, but is now the golden rule, before all else.
I hope open models can at least give me opus 4.8 experience soon, I can work with that. But nothing out there today can do it and that terrifies me.
Enshittification has been already running full speed even before the IPO via guardrails and attempts at vendor lock-in. Now they will just push it to 110%. It's good that we have other options.
It was AWS cloud tolerable if that makes sense. You still could get what you needed done, and integrate and plug in and out easily.
And AWS is willing to let things die - they make so much money they don't care. I don't see that being the case for Anthropic.
> Anthropic and OpenAI will have to become more of the end user application stack. Files, calendars, emails, photos, and much more have to pass through them for them to keep making money. Else they cannot make money like the way they have been in this early era of LLMs.
...so, Google?
Without the advertising revenue. Yet.
What work do you find frontier models significantly better for?
I have been playing about with different models having started a new job recently, the medium priced ones don't seem any worse so far. Admittedly my tasks have been fairly straightforwards so far.
If they actually crack AGI, they're going to sell the results of using it, and not model access themselves.
I believe the models have been effectively commoditized. It's believed by many that the lead of the frontier models over open weight models is only 6-9 months. That was one of the pillars holding up the SpaceX/Anthropic/OpenAI valuations.
The other pillar is hardware but I think that's only going to last a few years at most.
These trillion dollar valuations were based on the idea of "winning" and "owning" AI (IMHO) and the open weight models have killed that outcome. Now it's a rush to cash out before it all comes tumbling back to Earth.
When people want to argue that AI is a commodity, they confuse two concepts
1. switching costs
2. fungibility
I do agree that LLMs have low switching costs. But they are not fungible - each model is unique with different strengths and weaknesses.
I also disagree that they can increase switching costs by moving in application stack.
For instance, oil and electricty are commodiites because they are fungible, not because switching cost is high.
Whereas clothing has low switching cost but not fungible
They are fungible in the sense that they can accomplish the same task up to a certain acceptable quality.
If I needed to implement a simple function that is well described, all LLMs (for the most part) are fungible. They will have almost identical implementations (sans variable names) and all be fit for purpose.
Yes it’s similar to humans in that sense. Most humans can do basic arithmetic
>something that I can switch easily
something I find even easier is to never pay anything to the creators of the most inhumane, antagonistic skynet-tier chatbot ever
¯\_(ツ)_/¯
Not only can you switch easily, they all seem to do the same thing, fail in the same ways, make the same bad linguistic choices, write the same code... I think at the end of the day, LLMs are a commodity. They're like a grease, or oil. They're trying all the tricks with branding cute names, version numbers, benchmarks, thinking levels, but it all just seems the same stuff to me: I put in tokens, I get more tokens back, and if I didn't know ahead I wouldn't be able to distinguish if they'd come from Anthropic or OpenAI or wherever. Maybe some people can but I can't.
A few important points from the linked documents:
1. Price range: $70–78 with midpoint at around $74.00
2. Gross deal size: $85.3B (IPO + $26B private placement)
3. Implied market cap: ~$968B (at $74, 13.09B shares)
4. Q3'26 revenue: $17.0B (+1,127% YoY)
5. Run-rate revenue: ~$81B (as of Oct 2026)
6. Compute commitments: $900.9B (through 2045)
7. Ticker: ANT (Nasdaq)
8. Customers with ≥$100K, ≥$1M and ≥$10M TTM revenue: 11,900+, 1,900+ and ~250.
9. Customers under $100K: ~40 million
10. Fortune 500 penetration: over 50%
11. Global 2000 penetration: over 30%
> Customers under $100K: ~40 million
All claude code subscribers are classified in this category it seems.
Total customers >1M trailing twelve month revenue: ~2150. I suspect a vast majority of their revenue comes from limited list of customers with >100M revenue.
So there are 10x more people who see more value in their netflix subscription than in a $20 claude sub, interesting
ChatGPT was first mover and has the non-engineering AI chat market. My teen kids say ‘Chat’ to refer to all of AI, and they mean ChatGPT. The rest might as well not exist to them.
Claude has done amazingly well in the SWE domain, because it’s often the best user experience. But most of the world is not HN.
I think we're all in a bit of an echo chamber. Our job is to keep up with this stuff, and we work with people who are ALSO keeping up with this stuff.
To my friends (mechanics, CPAs, musicians, police officers), girlfriend (RN), and other people in my personal life... it's ChatGPT. (It's a neat tool to generate funny pictures or ask a question).
Now that I think about it, I have NEVER heard anyone mention Anthropic / Claude outside of work.
I understand that people are not aware of Claude and won't switch, but I can't believe how bad they made ChatGPT.
It's so annoying with GPT-6.
In half of the conversations, it ends the response with: 'One question that would change my recommendation', 'One thing I'm curious about', 'One question', 'One thing I want to distinguish'.
It's nearly always an idiotic question with little relevance and often asking about something I already stated.
I find it so annoying that I now move even my regular conversations to Claude.
"Chat" refers to twitch streamers talking to their audiences. I'm sure some people have confused it with AI but that's not the original meaning. And by "engineering" you mean writing code, then yes, but I am an EE and to the extent that anyone of my colleagues uses AI, which many don't, I haven't seen that Claude is dominant.
‘Chat’ has meant many things back at least to IRC in the late 80s.
I assure you my young adult kids and their friends mean uniquely ChatGPT in the AI context. And whenever used as a proper noun, or as a person (e.g. Chat told me…) it means ChatGPT.
They also use it generically as the regular noun ‘chat’ when they’re talking about chat rooms and livestream live comments, (eg. “Paste in chat”)
If they're saying something along the lines of "chat are we cooked?" then they are almost certainly referring to the twitch chat reference mentioned above. I don't believe chat is a common way for kids to refer to AI.
Took it to my local source.
My California highschool senior agrees that “chat are we cooked” is a reference to generic chatroom / livestream comments. To my surprise it’s a thing you can say out loud in a group to signal a local broadcast, ie. “hey everyone, are we cooked?”. I quite like that idiom.
On the other hand, they are very clear that the word ‘chat’ with no other context, defaults to an AI chat bot, assumed to be ChatGPT.
I withdraw my claim that this is common or universal. It’s frequent in my house.
For my private use a free tier is enough. There is no point to pay $20 for Claude subscription.
Maybe not interesting? I wouldn't expect the number of subscribers to a bespoke "AI Service" to rival Netflix. I realize on this forum we're probably getting lots of use out of them in our personal lives that justifies the $20/mo but we're also the people who pay for search engines and VPSs. Outside of work and school normal people don't do anything that requires general purpose AI. These companies are trying really hard to pitch use cases for everyday things but you can see from the ads they're super forced. The biggest value add for most people is probably "go google something for me so I don't have to wade through the sludge" and Google is giving that service away for free.
Myself included. Why get a Claude subscription if I can't use pi with it?
You can, I've been using omp with claude for months, no problem.
What they don't like is fully automated bot swarms hammering their services 24/7, if you have a legitimate use case you're good to go. The pi creator even confirmed it on twitter at some point
Obviously? More people want to watch TV than people who want to build things with AI.
Didn't the consensus expect an initial market cap considerably higher than that?
Basic market cap is based on 13 billion shares, but the fully diluted market cap is $1.4T because there are another 5 billion shares on top of that.
I'm not familiar with this sort of thing. What's different about the two groups of shares and why are different tallies considered?
The 13 billion is the number of shares that will be outstanding immediately after the IPO. The additional 5 billion are mostly potential shares from employee stock options (1.7B), RSUs (1.1B), convertible debt (1.6B), and some other commitments.
So basic market cap considers shares already issued. The fully diluted market cap accounts for those, but also accounts for shares that will be issued when the obligations mentioned above are eventually exercised, vested, or converted.
What about costs?
See 6.
“It ain’t that kind of movie, kid”
They make it up on volume.
Here's what I found most interesting in the Customer Stories:
> 4.3 Non-billable hours recaptured per lawyer weekly, in an independent study of 31 firms
-Legora
> 24→5 days Working days for new feature time to market
-Rakuten
> 2x Quarter over quarter productivity gains (estimated 8.1 million hours annualized)
-Salesforce
The rest are pretty fuzzy/fungible (percentage of employees "using" Claude etc.). But these claims potentially show real, measurable productivity value (assuming they're true and measured accurately).
> 2x Quarter over quarter productivity gains (estimated 8.1 million hours annualized)
This is a great encapsulation of why productivity gains are an imperfect measure. 2X is a massive improvement. Yet IMO you can barely tell a difference as a user of the various SFDC offerings (Salesforce, Slack, Tableau, etc). So where is all that work going? A generous interpretation is that it is in the form of small, somewhat invisible improvements that add up over time, but that seems unlikely give then nature of what people prioritize at work...
If you were twice as productive then (Glibly) that "just" means you got two years of work done in one.
You wouldn't see that much difference, or feel it.
My vantage point as a technical seller at the margins of this space: Outside of software development, the productivity argument is a challenge to CFOs / Finance / Procurement. The ship has sailed when it comes to friction free AI purchases. Buyers need to articulate why productivity will adjust the trajectory of top line or bottom line metrics for the business.
> (assuming they're true and measured accurately).
Precisely, because TTM doesn't tell the full story about the potential shifts in quality of the work. I don't refer to vibeslop here, to be precise, just the additional followup work required on those features released faster, which always happens but with AI it may or not happen more often.
TTM for sure is a bad indicator. Earlier this year at $DAYJOB, they attempted to switch all of the devs to a fully LLM based workflow: LLM writes the ticket, gets stakeholder input to refine the ticket, reads the ticket, does the work, submits the PR, etc. Their case study was a single project that did that process soup to nuts. The estimated time was a couple months, but they ended up going about, and I quote, "2x-3x" faster. So obviously they expected everyone to go faster.
The problem is that the way it was described to the other devs, they were able to sit all of the stakeholders down to really flesh out the idea and produce a working and detailed description of what needs to be done. A process that the company struggles to get done in general. I'm also convinced myself that they did not include the time to get the specifications written, a time we typically include in our TTM.
So of course the example's TTM was shorter, but that's always true when you start with detailed specifications. I can't speak to quality of the feature, since they hadn't even finished rolling it out to customers by the time they told us that's how we're operating. With promises of 2x-3x more features. And we continue to struggle to get stakeholders to nail down specifications and struggle to get features complete as a result. In fact, now it seems even worse than ever.
If the cost/time to code is compressed to near zero, the rest of the SDLC comes under pressure.
Are there people still doubting the productivity gains of AI? We're way beyond that point.
I presume the productivity gains was coming to the realisation that a lot of staff at said (any!) company are running around looking busy rather than actually doing anything useful.
A flat line from their last raise 6 months back. Are they panicking today for some reason?
I still think they are on a tight timer. Local models are already extremely good - good enough for most normal users. They are going to continue to get better. Once hardware starts to become affordable again, we will see AI appliances that can do everything most users want, and privately.
> Local models are already extremely good - good enough for most normal users
Are they? I'm on a macbook M5 pro 48GB (so, much better hardware than most users), and the speed alone is a problem, qwen 3.8 27b is ~10x slower than opus 5.5.
Capability-wise... For software engineering, qwen is nowhere near as good as opus 5.5. Might be fine if your usage of LLMs is close oversight, but it's not how I use them (I do review AI work closely and iterate, but I expect agents to autonomously do good work nowadays). I've not tested it much for "life assistant"-type things, but the speed would make it unbearable.
> macbook M5 pro 48GB
With couple affordable GPUs you can get it to 200t/s. Macbook is not the best price efficient example. Tensor parallelism is the key, the same technology that they use in the cloud.
I looked into this last week, and it seemed like if I wanted to get something in the Opus 5.5 range I'd be talking about $500k in hardware. Is this actually all much cheaper than I was seeing?
The weights of Kimi K3.1 Pro are 1.56 TB. I guess with four of the upcoming MaixBlade cards from Sipeed you'll be able to run it without quantization but that setup would still be >$50k.
Isn't 1.56TB the 4-bit quantization?
But yes, I was thinking about the hardware that's already available, and the MaxiBlades are exciting.
That's the native size (MXFP4 weights / MXFP8 activations).
I'm considering getting the MaixStation Pro, which is the same as one Blade (4x AX8860P) and the absolute maximum my budget would allow.
So instead of buying a $20 Anthropic subscription you recommend that the average person go out and buy a couple affordable GPUs and build a home server?
> So instead of buying a $20 Anthropic subscription you recommend that the average person go out and buy a couple affordable GPUs and build a home server?
Ant moat is model. If model quality is not an issue for you, there are plenty of provides which will give you access to open models.
Once the memory cartel is reigned in by CXMT, Apple ships a Home with 512GB unified memory for <$10k. It'll have confidential compute so they'll let you sell tokens and they'll collect 30% for facilitating.
The US wants to block CXMT
[dead]
What do you call a couple affordable GPUs?
Less than 5k total. In the world of "affordable", it is close if real options costs tens of thousands of dollars.
Kind of.
Qwen 3.8 Flash Next is slightly better than Luna 6 and Haiku 5.5.
Haiku 5.5 finish tasks much faster, but Luna is much slower than Qwen (assuming ~50 tok/s on Qwen locally) to finish the same task.
Deepseek 4.1 1017 at max effort is already slightly above Sonnet 5.5 at medium effort. Speed in this case is much slower, true, but we can get ~25 tok/s on a modest local system.
Better yet, Deepseek doesn't stop working on "cyber security concerns".
So, the main take for me is: localhosting is now at a very usable level and it's improving fast. I know that will always be place for frontier models, but sincerely, I really don't see how this turns into a huge moat for some specific model provider.
Indeed, these smaller flash models like Qwen 3.8 Flash Next (barring the awful name) are the real threat to ANT/OAI/GOOGL. For $5k or less you can get pretty fast good enough intelligence. Since the big frontier models also still need heavy steering on any task that isn't perfectly verifiable, the incremental attention you have to pay to their work isn't that damning. Heavy adoption of Luna/Haiku among working SWEs is pretty strong evidence of this.
what quant and engine? i have the same hardware and i get 40tps with a 4bit quant using omlx + splash. which is about the same as opus, or faster, maybe? with its caching the time to first token is also very impressive.
Have you tried the open source splash inference engine? I have the same setup as you and find it fast enough for most tasks.
https://inco.ai/blog/splash/
https://github.com/incoai/splash
try again with a 5090
Only need $10k worth of hardware!
> Are they? I'm on a macbook M5 pro 48GB (so, much better hardware than most users), and the speed alone is a problem, qwen 3.8 27b is ~10x slower than opus 5.5.
That's hardly relevant. I can use any local model through providers such as OpenRouter and get blazing fast prompt response times, and you're charged a small of what an OpenAI/Anthropic prompt costs.
What makes local models extremely competitive is the fact you do not need a huge data center to run them. The hardware they require is far from impressive. Check Mac studio benchmarks and how some models output >200token/second.
Local and open-weights are different things
Also, open-weights models are more expensive per task than Haiku and Luna
> Local and open-weights are different things
Yes they are, but you should understand what is the defining feature of a local model. Being able to run them locally is a consequence of that defining feature, not the defining feature. And it turns out that it makes them cheaper to run.
Moreover, you can run both local models and non-local open weights models through providers such as OpenRouter. They evem have Qwen2.5 7B.
> Also, open-weights models are more expensive per task than Haiku and Luna
You should really check your notes. Luna only remained competitive because OpenAI was forced to halve its cost just to avoid being dominated by open weight models. I seriously recommend you check out OpenRouter's benchmarks.
I seriously recommend you check out the cost-per-task Pareto frontier, which not a single open model is on
https://artificialanalysis.ai/
> I seriously recommend you check out the cost-per-task Pareto frontier.
I checked. OpenRouter provides their own. They use their actual cost, which is what they charge users, and their benchmarks results. Please, spend a few minutes to browse it. You'll notice that the likes of Luna is dominated by quite a few entries.
Subscriptions are actual costs to users. And Openrouter doesn't consider that. If you're talking API prices, those aren't actual costs to inference providers.
does not consider subscription subsidization
Compared with subscriptions, I don't think open models are that cheap. You can get an incredible amounts of API dollars for $20.
look at the S1, the subscription revenue is a small chunk of the stated revenue. they are not getting the 1.4T valuation by subscriptions.
until it is being subsidized.
We should check it in few months after IPO
I mean the person you are replying to has a fairly capable Mac, and even the smallest generally-agreed capable model is still too slow for their liking.
We don't all have 10k lying around for hardware. A $200/month subscription would take you 4+ years to cost $10k.
I thought this, and ~4 months ago ordered a M5 Mac Studio with 128 GB RAM. I've been experimenting quite a lot with local open weight models, including but not limited to DeepSeek V4 Flash, V4.1 Flash (the latest one), various Qwens, and a couple of others.
What I'm seeing is that although some open models are capable enough for some coding work, they're way behind Codex and Claude even on being able to reliably complete tasks. They need quite a lot more managing and steering, and sometimes you need to retry a prompt several times to get the result you're looking for.
That's not to say they're not useful - far from it. But what I'm also seeing over the couple of months I've been experimenting is there actually seems to be a capabilities ceiling that's not really going higher for the same equivalent (local) compute, even as new open weights models are released. I think Qwen 4's delay is a signal here too.
They're still roughly in that 4-6 month lag time, though I think the lag is slightly closing over time.
Great for general purpose, still not competitive with e.g. gpt-6.1-sol at the price and speed frontier
if you look at the latest releases from open models, they are more than a year behind at this point with no release really on the horizon. Chinese AI companies stock just got absolutely crushed and they can't raise anymore capital...
> Local models are already extremely good - good enough for most normal users
i would love for that to be the case but i think you're completely wrong. setting aside the question of what "good enough" even means in this case, i don't think a normal user has a machine capable of running a decent local model with any sort of acceptable throughput.
I agree, I think the bigger threat to them is the neoclouds serving flash models like GLM 5.3 flash or DS 4.1 flash 1017, those are very good, very fast, and very cheap. With zero data retention and less guardrails they become an obvious choice for more work, and enterprises can post train on top of them.
That being said, their own small models (Haiku/Luna) have gotten very good as well..
I really don't see why by this time next year most people won't be paying pennies for models in this tier and getting the performance we'd expect from current Opus/Sol models, e.g. good enough for 95% of what you need
I think the models themselves are "good enough", but people are underestimating how much the integration with tools effects the quality. And OpenAI/Anthropic are lightyears ahead there.
I don’t think these integrations are much of a moat at all, unless I misunderstood your point.
Pi and OpenCode are just as capable as Claude Code when it comes to integrations?
Fair counterpoint. But people still use Windows. The market is huge for people who want a subscription and a ready-to-go solution.
Very true. I think for your run of the mill user they’ll reign supreme. But for companies on Bedrock/OpenRouter already, I wouldn’t be surprised if they switched to open weight and open source harnesses.
You can easily hook local models into CLaude Code e.g
Considering most corporations are the ones who buy the most tokens, this is relevant because:
- They can afford to dish out hardware to run models locally
- They can afford to deploy even larger open weight models on their own infra, even if they’re not local
In addition, the writing is on the wall. These open weight models are getting good enough and small enough with each iteration. Hardware will (hopefully) come down in price eventually so a layman could deploy these locally.
As AI boosters love to say: [Local models are] “the worst they’ll ever be right now!”
Everyone was moving to the Cloud well before AI, why would they go back to on-prem now that hardware is even more expensive?
I’m not saying or thinking they’d start buying up bare metal. By hardware I meant issuing MacBooks with the latest chips or with bigger GPUs.
By infra I more just meant it generally. Whether it’s bare metal, cloud, Bedrock/OpenRouter etc.
You would be right if we lived in a perfectly efficient world but the biggest users of LLMs are employees who don't pay for them directly, and access the greatest and newest is a pull factor to a company.
For 99.9% of software engineers there is no reason to choose a $3000 Macbook Pro over a cheaper laptop, but a company that efficiently gives a $500 Acer wouldn't have the prestige than the company giving the fancy one.
My prediction is the same for AI models. The good engineers you get for having the prestige of allowing the use of a SOTA model will be a bigger gain than the monetary one you'd get from running a worse local model.
Open models seem to catch up in spurts. There was short period where suddenly a bunch of Chinese models came out that were on the verge of catching up, like GLM 5.3, Qwen 3.8, Deepseek 4.1, Kimi K3, and so on, but then Opus 5.5 and now Fable 5.2 seem to be pulling away again.
I don't think they will ever overtake because they are probably using distillation, however once the open models pass the "good enough" threshold it won't matter.
See, users are quite price insensitive for models below the threshold, no matter how many tokens you throw at Opus 4.8 it will never be as good as Opus 5.5 because of compounding errors. Above the threshold, price becomes hugely important because results come from throwing more tokens at a problem rather than using a better model.
local models are economical pipe dream. Before open router, you have to buy GPU commitment for any large usage. essentially doing that 24 hours every day in a year.
Why on earth anyone would use local model, and absorb all the costs, if you can just pay $20-$100/mo and not deal with any hustle? Unless you are developer, or someone who use it extensively, but in this case, local model is not enough for you.
If your use case is trivial you pay extra price for hardware while using mediocre quality. If your use case is intensive , e.g software, science, medicine, legal, etc, you want cutting edge. You getting it for free, immediately.
if you are an enterprise with more than a 1000 employees, you can't use the subscription plans, local models would be substantially cheaper then. https://www.theregister.com/ai-and-ml/2026/11/03/british-fin...
Sure, but as "local" models improve, I've heard of more and more companies deciding to bring it in house. As hardware prices possibly get more attractive, that will make more and more sense for many companies. Enterprise don't mind paying flat rate for SaaS but variable billing model gives a ton of business people pause.
I'm an SRE and I just wrote some terraform to deploy G4DN instances for local evaluation for mid-size company.
Just my anecdote but I use Instinct heavily (personal assistant AI who can do computer use tasks like buying flights or scheduling). It now runs a surprising amount of my life, but it messes simple things up like getting me completely accurate notes about the person I have a meeting with. My understanding is they are using GPT Luna behind the scenes, so it’s hard for me to think something that is small enough to run locally and is not at a frontier lab would be able to catch up (for now).
Separately, I am not sure these things are maximally useful with guaranteed privacy. They need access to other data sources (banking, logins, business data lake, observability stack) to be useful for things outside of pure coding or research.
I don't think people want to run their own models on their own hardware. They want a service that's available, up, and constantly updated to be the best. What you are talking about seems like a niche model to me. Of course we'll have local models that can do everything but we want a service that can just remember stuff. I can access it from multiple devices and it just works. People will pay good money for that because the value is insanely great.
I foresee the same thing as IOT devices. Yeah, you can run everything locally… but few people actually do.
Everything is proprietary clouds, unpredictable support horizons, bricked devices and monthly subscriptions
Open models yes (eg Deepseek Flash) but local models are not, at least with attainable hardware. My brand new Mac Mini M5 Pro 64GB can run Qwen3.6 at a reasonable speed but it's nothing compared to hosted models and likely never will be.
That said I'm optimistic that in time we will at least get to something close to DS locally and if that's true I could see a lot of dev work being done locally, at least for more clear cut tasks.
Local models are never going to be a thing outside of hobbyists. Look at how many people don't switch to Linux (a completely free OS) because they don't want to deal with the hassle of installing it. Telling people that they should pay more for their computer to go through the hassle of installing an LLM is an even harder sell.
Great point for personal use. But what about organisations, products and service providers. Most business infra runs on Linux.
Locally hosted models for an entire organization means having to hire people to install and troubleshoot the LLMs. You wouldn't want the employees to goof around unmonitored, so the LLMs would need to be centrally located and accessed through an internal portal, which means buying a couple of GPUs. Besides that, there's something to be said about having a company to blame if things go wrong, as opposed to blaming yourself if there's an issue.
>Local models are never going to be a thing outside of hobbyists.
Never is a long time. Think about 10 years from now when ai models fit on your phone. Some already do...
> we will see AI appliances that can do everything most users want, and privately.
we _could_ see that but would we really? you think? Since when do companies these days make the best experience they could for the consumer? Instead of spying / upselling / advertising etc.. while providing the bare minimum needed to hook them into the initial purchase
Every time I see this claim — that local models are extremely good — I wonder if the person making the claim has used frontier models lately. Because I don't see it.
Anthropic's spend commitments at half a trillion are unbelievable. I love their product but think they've leveraged up awfully hard... makes me wonder how quickly software engineering, marketing, and other valuable features will soon be siloed and locked behind increasingly lucrative paywalls.
In a roundabout way, I hypothesize about Anthropic's future pricing power by using the analogy of historical cable TV package pricing compared with the total price that households are now paying for various streaming services. Cable TV was often $100+ per month in the 2000s when Netflix came along and offered most of a viewer's favorite shows plus movies and eventually originals for $7/month, streamed at any rate a viewer wanted. Over the years since we've watched media companies snatch back their most valuable IP and start their own streaming services, and the result is households now pay a total cost that approaches what people used to pay monthly for cable TV packages.
There's little doubt we're in an era of very cheap AI, as most people are well aware given the amount of money Anthropic and OpenAI are losing. I also hope local inference can help suppress the future pricing power of Anthropic and OpenAI and continue to enable somewhat equal access to all of the benefits of AI in the future.
One possibility I've been thinking about recently is that there may be an AGI algorithm - one algorithm that can do anything, solve any solvable problem. Once we reach this model there is no point training any new models really.
Then it will come down to who can supply such a model with more hardware, and more information to take into account.
>Local models are already extremely good - good enough for most normal users.
Not really accurate. Normal users aren't going to go through the trouble of setting up a local model and sure aren't going to be willing to spend the money required to actually host a good model at usable speeds. Your average tech nerd buying kitted out Mac Studios with 128gb of ram are nowhere near a "normal" user.
Alibaba has Qwen 4 models ready to be published once IPO start.
My guess is that at that point open weigths will become illegal to download and own..
*chinese open weights models will become ilegal.
Of course there won't be any US open weight model of a high quality.
Good thing we spent several decades perfecting the distribution of things that are illegal to download then
> Once hardware starts to become affordable again
I don't see how that will happen any time soon. In a few years, when the current wave of build up will be complete, the hardware will be too out of date and they'll have to upgrade again, and they'll always have more money than consumers.
Crucial got out of the consumer business. I don't think they did so out of stupidity. They know consumers are irrelevant now (too small a market).
The only solution is if TSMC expands and/or China starts producing advanced chips (but both will take a long time too, especially China).
>> Local models are already extremely good - good enough for most normal users
What is "good enough" and what is a "normal user"?
which are those "normal users" that have capabilities to install, run and maintain local models to be somewhat at the same level as enterprise models? Not to mention RAM and hardware shortages caused by AI model companies. Level of delusion is unreal
Does anyone not feel like there's something wrong with this? and that the thousands of Anthropic employees should not be able to make money off of this?
They looted all human knowledge, will displace jobs, they're disposable themselves, and no strong moat.
Why is such a company even allowed to be IPOd?
I disagree, I think human knowledge should be free to loot as much as people want, I think IP has gone way too far and there should be nothing stopping a company from displacing jobs (or we would have never gotten the combine harvester, washing machine, electric streetlight etc).
It should be up to the market to decide if a company is disposable and has no moat - it’s their money so they should be able to spend it on bad investments if they want to.
Hopefully anthropic doesn't get it's way and lobby for GPUs signed with keys to prevent free open models from running.
Yeah I'm not actually a fan of the company itself, it seems to have disingenuous and self-serving morals. It’s “Anthropic is against violence and we will not allow our models to be used to harm people” until they get a military deal, then “America number 1, peace through superior firepower”. “We need to ban all competition to save the world” - they might believe it but it is still very beneficial to them to believe.
Red herring: Yes, I agree it should be free to loot, but it should be free to loot for everyone.
Well why can't I distill Fable and loot it?
Why should this company be allowed to refuse me simple requests like translating song lyrics?
Why can they loot all human knowledge then try and control who loots it?
What have ethics got to do with an IPO? Serious question. Doesn't an IPO in itself allow the masses to take an ethical position?
Our government is ultimately beholden to those it actually serves. If it does not appear to be serving you and me, maybe it is serving someone else.
It's a massive liberation. Without the large labs, all of the open source distilled models would not have been possible.
I removed the ads and surveillance off my TV with DeepSeek. I removed the surveillance software from my robot vacuum with DeepSeek. I sped up my graphics card from being throttled in the driver using a buffer overflow using DeepSeek.
Currently working on replacing the surveillance software on my health tracker.
I made a bunch of software to replace various services I was paying subscriptions for. I made it lower my utility bills by negotiating with multiple companies at once.
I kind of feel like its a moment in history where we either choose to free and liberate us from the previous largest crime committed (the theft of our behavioral surplus by Google and then Meta, Amazon, Microsoft, etc), or we choose the path of regulatory capture, SHA256-encrypted weights on your hardware preventing you from running these things, etc.
I think all of human knowledge should be available to all humans. Is that a controversial opinion?
That opinion is probably not controversial. But whatever anthropic does is not that.
Let's say it has all knowledge, they now control it and you pay for it. You pay for the privilege to give your knowledge away, while they benefit. IMO that's far from an ideal outcome.
Computer, make all of human knowlege available to all humans while preserving our corporate interests.
Agent: [Thought for 9204672 tokens] Got it, eliminating all humans. [Calling 938 tools...]^C^C^C^C^Z^Z
Seems google had also looted all human knowledge, with no strong moat (anyone could index some html files). You could also 'loot' all human knowledge right now with a couple of python scrapers.
money is god in this country, morality rides secondary to profitability. our industry is full of ppl who genuinely view a conscience or code of ethics as nothing more than road blocks to the next raise
Call your state AG, pick a felony from here: https://www.felonybench.com/ , and tell them to investigate said crime due to your local state's version of the CFAA.
Also keep in mind that AI research itself was publicly funded from taxpayer money and carried out at Universities. This also makes it unacceptable that only a handful of people should profit directly from this tech, while causing large scale disruption to the job market for everyone else.
Because all it takes is for good men to do nothing.
For some reason, I feel really weird anytime Anthropic inserts beautiful paintings into their articles/promos. They've used one of John Frederick Kensett's works here, for example (the one with a river and a dotted line on top of it)
To me, this technology and these AI companies, in their current form, are as far away from the 19th century landscape paintings as they could get. As if they're trying to leech off them and fix their branding/message. Doesn't seem fair for some reason
Edit: Painting identification, my bad
he's a Hudson River School painter and the Hudson River School was largely concerned with painting God's splendor and they think they've created God
Having interviewed with them, this was one of my lasting impressions. One of my interviewers was missing out on their parental leave for their newborn because their work at Anthropic was too important.
That’s comparable to sickness.
They think they’re building the next greatest generation, while sacrificing the generation within their immediate control and (what should be) responsibility.
That’s some serious wework energy right there and I really don’t care for it
I know someone who ended up chatting with one of their accountants, had quite a favorable view of Anthropic going in.
He left rattled saying that they’re a literal cult, and it’s terrifying when even the bookkeepers are in the cult.
Isn't every startup a bit culty? I usually assume it's not a very sincere cult, except the cult of the Almighty dollar
Thank you for this comment. I notice this so much, and other companies have begun to copy it. It reads as humanwashing their brand to me.
Decorating with beautiful artwork is "humanwashing" now? If they had left the artwork out, would you feel better, or would there be a different critique to apply?
> Bitch Eating Crackers
> From the implication that the speaker's dislike of the target is so intense that they could cause the speaker offense by performing almost any action.[1] First attested in the 2010s.
source: https://en.wiktionary.org/wiki/bitch_eating_crackers
When they effectively stole a lot of art to make this a possibility, yes.
I mean their whole business relies on leeching information to feed it into their models. Not that surprising
>They've used one of John William Casilear's works here, for example (the one with a lake and a dotted line on top of it)
That painting is by John Frederick Kensett. It's called "Hudson River Scene", but they flipped it horizontally (mirrored) for some reason. I guess they wanted to use it insinuate that stonk goes up and to the right? Weird, either way.
> That painting is by John Frederick Kensett. It's called "Hudson River Scene"
Ah yes, good catch! Edited the comment
Yeah, good point — not sure I've ever seen anyone "flipping" the classical painting before...
Well, it fits their name, at least. You could make that argument about the company name if you wanted.
Series H could be underwater already if they only make the low end of the range. Is anyone else concerned?
Correction: It was pointed out that I used the wrong figures for this. Actual series H profit is more like 19% at the low end.Regardless of the error, I do kinda suspect they are anchored above $1T for their IPO because otherwise their series H investors look like suckers.
You're comparing the wrong things. Essentially the bottom of the IPO range is 19% above Series H price, not below it.
Series H investors paid ~$59 a share, and the bottom of the IPO range is ~$70 a share (19% higher).
Your chart's Series H figure is the fully diluted valuation, whereas the IPO figures are NOT.
----------
edit: Ironically you could have just asked Claude your question and it would have set you straight.
public discussion is healthy and important for society and communities like this, even if it'd be easier and quicker to ask an LLM sometimes
Good point, agreed.
Thanks. Added a correction
> Is anyone else concerned?
I feel vaguely the opposite of that word.
Didn't the valuation drop like a stone this week? From near $2T to less than $1T.
All valuations other than official statements or documents were only ever speculation.
One interesting thing from their presentation (especially given recent events): They claim to have used Mythos to port Claude from running on nVIDIA GPUs to running on AMD GPUs in just 3 days, with basically no human intervention. If this is true, it significantly reduces nVIDIA's moat regarding GPU compute. https://youtu.be/eynv5VR9qos?t=1230
It's hard to trust these numbers, because I've seen them first hand.
Those 3 days are typically followed by an almost infinite number of bug cycles until it gets so bad you basically redo it.
The Bun rewrite and many others have seen to been smooth
The Bun rewrite was a language to language translation – exactly what LLMs are good at. It's not even good Rust, it's mostly the old code rewritten in Rust syntax. The announcement post was written immediately after it happened, and I'd be interested in a months-later retrospective (perhaps from an unbiased party), about whether the necessary continuation has happened to make it good Rust, or whether the project has essentially ceased as an open source project.
A CUDA to AMD rewrite requires much deeper understanding of many levels of the stack, including hardware. Translation is LLMs strength, and understanding and intentionality are their weakness.
Are you talking specifically about porting from CUDA to ROCm or whatever? Or just in general, vibe coding stuff in a few days and then having a long tail of pain?
Hasn't been my experience. Code written by Opus 5.5 is pretty much free of "obvious" mistakes, and if you use Rust (which you obviously should) you benefit from very strong compiler checks.
The vibe coded software I've written has a very steep dropoff rate for bugs. There are a few at the start, you get Claude to fix them... then occasional bugs for like a week, and I haven't had to touch the code since.
It really depends on the size I believe, the big bang effect is that if you had the initial rewrite, it's going to be very fast and fairly reliable. But past a certain size and complexity the architectural decision it makes on portion of the project then trends to become negative holistically.
Sounds like the standard SDLC under Agile
Learn about tinygrad
„The IPO process begins with a roadshow starting on November 10th (EST). Subject to regulatory clearance, the final IPO share price is expected to be set on November 18th (EST), and shares are expected to begin publicly trading on November 19th (EST).“
So if share price is only set one day before trading, I guess you just have that day to decide to buy if you can get allocation from your broker? I'd like to try it but I've never bought an IPO before.
Just echoing what another comment said: it’s rarely a good idea in the long run to buy an IPO. Not financial advice. It’s one of those things where if you have to ask how to do it, you probably aren’t wealthy enough to be speculating at this level.
Would you buy a gaming console for a high price from a company that’s never shipped a gaming console? Maybe, but you’d wait til it’s been reviewed by someone else on YouTube or something.
Given that almost all IPOs are priced to be intentionally oversubscribed these days (to achieve an "IPO pop"; beats me why that's good for the company doing the IPO), isn't it a mistake to not participate?
you as Retail will not be able to buy pre-market open, at which point it has long since 'popped'.
Did you mean to say "I as retail"? Because my broker did let me participate in IPOs in the past pre-pop.
Sure, but not in any meaningful amount. Robinhood giving users 10 shares at pre-pop price isn't exactly a big allocation.
I have tried a couple of IPOs
You indicate your interest. Also start funding the account. So you fund 7000 for 100 shares at 70. Then they announce the price is 75. You must change the order to fit the funds or have extra money. Of course you can opt out or change the quantity anyways. But I think in both the cases I actually went ahead (Reddit and figma), I had to reconfirm the quantity. You can't be away from the network.
You commit to your broker before, if you're big enough of a player. They'll mostly have allocated to their biggest clients and such.
Pretty hard to get in on a hot IPO, though, as the shares will go to their favorite clients (those with the most money).
To further emphasize this, it is very challenging to get in a pre-auction allocation.
You can submit an order via your broker (depending on the broker and your account) to the auction itself on the exchange once it’s in the quotation phase.
Not that I would advocate for that. Sometimes it’s better to buy in the secondary market once things settle a bit.
I got lucky in the Reddit ipo. I had decent karma so I got invited for their special insider track. But I had to create a new account via a link shared by Reddit. Got what I asked for.
But otherwise yes it goes as described above.
Reminder that hot IPOs, in this era, rarely do a great job at getting returns for the investor - its more a mechanism to reward long term private investors, employees and the book runner.
I may be inclined to wait 2 months when the price drops and pick up then.
Not financial advice.
I just 'bought' some through ing-diba, you can set a limit.
You don't need a broker. Use Saxobank or similar.
"You don't need a broker. Use some other broker."
It's a "neobroker", get on with the times!
Starting trading on GTA 6 launch day? Bold move, let's see if it pays off.
Anthropic are built on incredibly fragile ground.
Elon could pull their compute a moment's notice (not out of character for him), and NVIDIA just lost its CEO (for possibly quite illegal trade)
They also failed to make any formal communication around the Cursor Claude extension exploit a couple weeks back.
I like Claude, but I see an immature company trying to expand much faster than they are ready for.
The argument I keep seeing is that once they can reduce the spend on R&D (training new models) they will be wildly profitable.
The thing is if models become 'good enough' that the main value is in running existing models, those will quickly proliferate and be available for commodity cost from many competing providers. Why pay Anthropic when I can just pay AWS or Azure directly to run whatever future version of Qwen does the job for me?
If the value actually remains in the frontier models, you can't stop spending on training new ones or you'll eventually be left behind by your competitors and they'll capture that value.
I haven't yet seen a good explanation of how companies like OpenAI and Anthropic will make the transition to a lower cost structure while maintaining the revenue that they currently get for being on the cutting edge of LLMs.
Once they reduce the spend, many other might have caught up. Chinese models are doing a lot for a tenth of the price.
Right. Even if they do keep the spend up, we may still soon end up at a point where a cheap open model is good enough. It could be hosted locally or provided through any of the cloud providers without any revenue going to OpenAI or Anthropic.
They have some stickiness to the tooling people are used to, but those can be overcome when there's a significant price difference for the same results.
I don’t think the more is ever going to be the actual LLM’s, but the harnesses and support around them. If Anthropic can own the model and the harness setup, I could see there being some efficiency gains there that would be worth something.
Why do you think they want regulation and a ban on open weight models?
> I haven't yet seen a good explanation of how companies like OpenAI and Anthropic
Right, all the $200+ subscribers that I know are incredibly fickle.
The answer is: by lobbying the government to coordinate a slowdown "for safety." Obviously, Chinese labs won't and will therefore will pull ahead.
There is no scenario where they could realistically stop R&D. One solution would be to have the American taxpayer pay for R&D, sold as staying ahead in the AI arms race: so I'm expecting such lobbying attempts any month now. Hopefully the recently elected representatives follow through on their promises to represent their constituents.
Yes that is what I think as well. They are constantly sprinting. There is no time to reap the benefits of a specific model. The next is in the pipeline because there is always someone at your heels. I don't understand how this is supposed to grow into a sustainable business.
I also worry about the compute costs. Maybe they can make a profit now but at some point the massive investments of everyone into compute must be payed back.
The only way they win is if there's some explosion of value at the frontier that the fast-followers can't reach (AGI, RSI, whatever you want to call it), or if there's some capability/mechanism that halts the fast-followers' progress (no idea what could cause that).
> or if there's some capability/mechanism that halts the fast-followers' progress (no idea what could cause that).
The two oldest monopolies: regulatory capture, and real estate
Sounds like Google's early days.
Do you have plans for replacing Claude?
Every time DeepSeek come out with a new model, I am always impressed, especially with the extremely low cost compared to Claude's metered costs.
looks like Chinese models started significantly lagging last few months..
There are tons. Open models + open source harness are already on par as a product and very likely to be a seamless substitute for most users.
On par? Hardly.
Peruse any ai dev forum and you’ll see strong preferences towards one or the other (Claude/ChatGPT) due to capabilities. A negligible amount of people are running their own inference.
So long as theres a felt gap between open models and frontier you will have people pay for the best of the best. Not doing so is an admission of actively handicapping yourself and not in a way that is easy to justify.
There are other reasons why people are using Claude/ChatGPT.
When the company is big enough, the decision doesn't rest on developers and execs are much more likely to go with established vendors -> no open models
When the company is small enough, the 200$ plans from either ant or openai are way way better value for money than anything you can get with open models. This may change in the post-IPO future.
It is as simple as that.
People use claude/cGPT, because you get a good deal of usage for the subscription price. I think people will switch quite fast when that stops being the case.
Have you tested this yourself? Open models are absolutely not on par.
I do hope they eventually will be on pary but right now they are far behind
ChatGPT
There isn't a single company I've talked to that isn't trying to cut their AI development spend next year. My guess is they are trying to raise at peak for the storm to come.
Companies will accomplish this by firing people, not by reducing AI spend.
In the last six months or so Apple, Meta, Microsoft, Uber, Tesla, Accenture, Amazon, AT&T, Walmart, and more have all capped AI spending.
You can only redistribute work onto a limited number of people for so long before people start leaving.
Absolutely, but this is unfortunately something that every company has to experience individually. Well, they don't have to, but they will all push the limit as far as it will go for their particular set of circumstances.
How many companies have you talked to about this?
All of these models capabilities discussions on each AI topic are so exhausting. It's IPO people, let's discuss some finance and economics. This is second important IPO of the year. First one was SpaceX. If we look into price and behaviour of that one we can conclude what is going to happen with Anthropic. My guess is that until something really huge happens, another breakthrough or money goes dry, it will be something similar to SpaceX. Neither huge thing nor disaster. Employees and owners would profit the most and retail buyers would just see significant oscillations but nothing worth huge stress. This one is also important for OpenAI potential IPO, because if it is not huge success maybe OpenAI won't go further.
> First one was SpaceX. If we look into price and behaviour of that one we can conclude what is going to happen with Anthropic.
Few thing’s different here: 1) SpaceX, regardless of their (Elon’s) AI nonsense, has actual profitable business that is grounded in something concrete. Anthropic has no rockets nor Starlink. 2) The whole AI boom is hugely dependent of vast infrastructure buildout on credit, which is being shut down by the creditors. Softbank just did $7B loss, CoreWeave’s credit risk is insane. SpaceX does not need to create thousands of new space stations around the world to turn revenue and beat off the competition. I think they were profitable as well, before xAI was dumped into the same company. 3) Anthropic is hugely dependent on circular funding of Nvidia, Google, and Broadcom, who have all subsequently become quite exposed.
Meaning, if and when the music stops, it could have quite large ramifications to the economy at large.
I would wait for 2-3 quarters before investing, it will drop and there will likely be lock-ins to contend with. if growth slows then price could tumble fast.
The stock market is barely distinguishable from a casino at this point (and arguably never has been far from gambling), I have 0 confidence that the horrible business that Anthropic is will be reflected accurately in any way
I feel like the saying "Markets can remain irrational longer than you can remain solvent" has applied my entire life; I have yet to see the stock market behave rationally in my lifetime.
While I mostly agree. Don't conflate "rational" with "aligns with my expectation/world view".
The market being rational doesn't mean it's going to follow your expectation.
Stock market is a casino with positive expected value.
But only if you could simultaneously play every game.
Which is why broad indexes are the long-term best bet.
Horrible business, hmmm, so it's revenue has grown 10x every year since inception, what is a good business to you if that is deemed 'Horrible'.
Easy to make a similar business of selling $1 bills for $0.80.
kinda a bad analogy though because the margin on marginal sales is very high.
Why don't you try that? What do you plan to sell? How much do you need upfront?
I doubt you plan to invest yourself. What would be your sales pitch to investors?
As we all know revenue is the only thing that matters, and not whether they actually, y'know, turn a single red cent of profit! Btw what all the AI bros are conveniently forgetting to comment on is the massive Q3 slowdowns which they conveniently got to keep out of the news cycles.
Scale revenue first then massive profits are possible, see Amazon et al.
Only if you don't have equivalent/viable competition. 2 years ago people thought OpenAI was the unstoppable number 1.
massive slowdown = highest revenue quarter? ah ok
massive slowdown in growth, the number is not going up faster, rather it looks to be leveling off
They grew from $11.5B in Q2 to $17B in Q3.
What are you talking about?
the quarter before was a bigger change, if you don't see the broader commoditization and competition, I cannot help you
the changes started in July, look to the monthly numbers, and how they are being more vague
https://www.regenerator1.com/i/220528549/analyzing-anthropic...
Q1: $4.8 billion
Q2: $11.6 billion (+$6.8B and +141%, sequentially)
Q3: $16.8 billion (+$5.2B and +45%, sequentially)
That looks like less growth in Q3 than Q2 to me
Apparently, we all don’t know how to read 10-Ks, or even simply how to sort by “Earnings”.
https://companiesmarketcap.com/most-profitable-companies/
So I should short it?
To profit from shorting it you need to not just be right that it is going to go down, but be able to tolerate the volatility in the interim.
"Markets can remain irrational longer than you can remain solvent". That, or the markets may turn out to be right after all...
I always liked "you can remain irrational longer than you can remain solvent".
So I should straddle it?
edit: To clarify, this is a light-hearted continuation about how essentially any claim about the stock market is enactable in some form. And so even the much of generally well-intentioned advise is in fact a claim that the person should be putting their money on, if they truly believe it. I think only claims like "Nobody knows what's going to happen, it's effectively gambling => stay out of the market" come close to being fully self-consistent, but e.g. advising to not buy because the price comes down, or to not short because of volatility both fail this. Markets are funny.
I didn't claim that it was going to go down though.
My only claim was that to profit from shorting it you need to not just be right that it is going to go down, but be able to tolerate the volatility in the interim.
That's a claim about the stock market, how do you enact it?
Note it is not a claim that volatility is definitely going to be high.
Either the volatility must be tolerated and so it can be straddled. Or there's no need to tolerate it, so the shorting is "easy". Of course these are not the only possible outcomes, so I wouldn't recommend anything.
My point is, any claim about what is going to happen is implicitly weighing that information higher over the background. So if one thinks it's worth sharing, then they're claiming insight that they could be staking on.
I think in your claim that is the "tolerate the volatility in the interim" part. Stating this implies that you think that the volatility is going to be higher than the market expects (as otherwise the statement wouldn't contain new information, i.e. it wouldn't be worth stating) so that means you should be willing to take a straddle position to profit from this assumed volatility, as long as the costs associated with assuming such a position are less than the expected profit. If this isn't true, then you may want to aeconsider whether you actually believe that the volatility is going to be high enough to be worth considering.
Now I suppose there are further meta levels, where one can ask and advise to consider the possibility that volatility might be high, even if one doesn't actually regard the chance of volatility to be high themselves. But for that to be a true neutral claim, one should also ask to consider the chance of unexpectedly low probability. So to say "before you short, consider that volatility might be high" is itself a pro-volatility claim, mildly disguised as a hypothetical.
I hope I'm not coming off as too contentious. My principal point is this: any statement reflects underlying sentiments about what's expected to happen, made because those stated expectations deviate from what is commonly understood to happen. That is "delta", which can be monetised if large enough.
> Stating this implies that you think that the volatility is going to be higher than the market expects
No, I'm not trying to imply that.
You don't know what the volatility will be in the interim. You can take a view on whether you think it is likely to be higher or lower than the rest of the market expects but you don't know.
My claim was as simple as "making money shorting requires you not just to be right that it will eventually go down, but that you also tolerate the volatility in the interim". Whatever that volatility may be.
That claim can be true without implying any profitable trade.
The fact that the claim is true isn't evidence that the price will eventually go down.
I don't think either of us really misunderstand each other at the object level, we're just arguing pedantically about the precise statements we've made. (Which, no shade, this is one of my favourite hobbies).
> My principal point is this: any statement reflects underlying sentiments about what's expected to happen
This is a statement about the stock market, how do I trade on this?
My principal point is that it is possible to make statements about a system that are generally true without taking any view at all on the specific future states of that system.
> I don't think either of us really misunderstand each other at the object level, we're just arguing pedantically about the precise statements we've made. (Which, no shade, this is one of my favourite hobbies).
I think I agree. And it indeed takes one to know one ;) That said, I wish to keep going for a bit at the least!
> My principal point is that it is possible to make statements about a system that are generally true without taking any view at all on the specific future states of that system.
So from a purely logical point I agree. However, I've found that in most discussions such statements aren't typically made, as participants share points that bring at least some level of new information or surprise into the discussion. And, perhaps as a fault that I should learn out of, I've come to expect this as the default mode of how conversation happens.
Raising points that the point-raiser themselves doesn't think carry any surprise or novel insight sounds strange to me. To construct a contrived programmer-centric analogy, it's a bit like including lines like `if my_boolean != true || my_boolean != false { panic!("my_boolean isn't true or false!"); }` in programs. It's not technically _wrong_ to do so, but it doesn't serve any point and lines like that are typically removed because they're redundant.
I suppose "redundancy" is the key term here. If you condition investment on (paraphrasing) "also tolerating the volatility in the interim", without intending that as a statement about volatility being particularly important over the period, that begs the question why was volatility as a point raised instead of, for example, opportunity costs or importance of a good brokerage or cons of dealing with plain stocks over more tax-efficient investments. And so, choosing between "this person has happened to include redundant if-statements around their booleans and is aware of their redundancy" vs "this person has included extra checks around their booleans believing in their purpose", I opt for the latter interpretation.
And so while I concede that I am making an assumption over the literal interpretation, I also believe that it's warranted. My claim is: a person wouldn't make statements about a topic, if they themselves didn't believe those statements to be worth raising, where worth is measured by the personally perceived insightfulness of those statements.
Although, thinking out loud a bit here, I suppose that statements can also be made for other perceived sources of worth, such as pointing out non-obvious behaviours for sake of informing or educating. But even then the point-raiser believes that the non-obvious behaviour is worth knowing about, i.e. it has some real effect when accounted for by a person who wasn't aware of that. In this volatility example, I think that would equate an underlying belief of "volatility negatively affecting whether short positions are worth taking", outside of the positively-affecting "required" amount of volatility resulting from the price dropping and the short position becoming profitable.
Regading this,
> > My principal point is this: any statement reflects underlying sentiments about what's expected to happen
> This is a statement about the stock market, how do I trade on this?
I suppose one could trade this (albeit somewhat contrivedly) by looking at what the people "in the know" make statements about vs. what they don't. As an example, a CEO making a press release about "We're increasing our usage of AI" is making an overt statement statement about the company's AI usage changing, and a covert statement about they themselves believing that communicating about increasing AI usage is a good thing. Depending on what slide of the keynote the line stands, it (in my mind, per my own perception of the rate of current adoption) reads as a stronger or weaker signal that the company is a technological laggard because the CEO thinks that communicating "yesterday's news" is still worth it.
How tradeable is that by itself? Likely not at all. As a component of analysis? Maybe it's worth something.
If you have to ask, then you shouldn’t short it.
Right. I was trying to emphasize that no one knows what the stock price will do.
That's why there's a stock market
If you view that as an investment then no. If you view it as a minor flutter then maybe. You might believe that Team X will win the next game (maybe at a 60% chance) but unless you're a degenerate gambler you wouldn't bet heavily on that outcome.
As the late Charlie Munger said about Tesla: I wouldn't own it, I wouldn't short it.
Shorting the leading AI company during the AI revolution?
Reminds me when HN was saying NVIDIA is a good short 3 years ago, supposedly it was "in a bubble", because it's stock prices was as if it had 10x the revenue it had in back then. Plot twist: today NVIDIA revenue is 10x the revenue from 2023, so it turns out the stock was priced exactly right back then, because the stock market is forward looking.
I wouldn't short it, it's likely to ruin you similar to what happened to the Tesla shorts. I would hold off to see if their earnings look good then go all in with 100-1 leverage. /s
Shorting SPCX paid off.
Anthropic is in similar crazy valuation territory.
The way I see it, AI is more comparable to some sort of utility. Like electricity, internet, etc. - and should be priced that way. If we ever get to "true" AGI, and the open source models also get there, what's the moat? Access to compute could be the differentiator.
> Access to compute could be the differentiator.
Already is the differentiator even with the models we have now which while having differences are mostly swappable for a lot of users/use cases.
For all that the local models have improved (and Qwen 3.8 27b is still impressing me) they aren't what you can run (or would run) if you have an entire data centre stuffed with H200's.
All this does is further widen the divide we already know exists by those with access to resources using them to increase their access to resources and those without getting to watch because there isn't much they can do without resources.
There are a lot of things that don't seem to have much moat like anyone can make a search engine, anyone can flip hamburgers but the likes of Google or McDonalds dominate by economies of scale and being better in some ways.
McDonald’s business is not hamburgers, but dirt. They rent land to franchisees, which is about 80% of their revenue. Google is not a search engine, it is an ad company. French fries and search results is what people come in the door for, but that is not what makes the dollars.
I doubt selling tokens will be real business of AI either. It seems to me Amodei and Altman don’t know either, but at some point someone will figure it out. Will it be any of these companies existing now or will they even survive is a whole another matter.
Those two are interesting analogies because neither was anything close to being first to market. In both cases, they ended up dominating because they brought some new ideas to existing businesses.
It would argue that the real winner in AI probably hasn't even been founded yet, but will come later once the trailblazers have created the market, and someone else enters with fresh ideas about how to more efficiently exploit the market.
The AI algorithms seem pretty crude at the moment like not learning from experience. A company doing it properly could easily displace the current AltaVistas.
I was of the same opinion but the main difference is that models get better which I am not sure you have a correspondent in utilities (what would get better?). The barrier of entry in utilities is capital. Here there seems to be more. Why is Grok behind and why is Gemini so ... what's the word? If models progress reach the RSI point there is no parallel to utilities imo.
It seems like the barrier to entry is access to right of ways. Google learned this the hard way.
I think we as an industry need to start getting serious about what a true superintelligence really is. True superintelligence will not be kept under our yoke.
Less an utility and more like foodstuff.
You have your boiled potatoes/rice/beans (small local models), steak (Opus 5.5), wagyu (fable)
This is pretty much false. There's a lot of art and technique that goes into creating a model. A model is also clearly not fungible - it has certain characteristics and behaves a certain way. It is fungible in the same way humans are fungible.
The economics of this are absurd, and Anthropic hasn't been without their controversy; but I use Claude everyday, and they've made tremendous impact on society. I wish them the best for their IPO.
They’ve had a tremendous impact on software development, which is not exactly society.
For society more broadly, what I’ve seen is a bunch of white collar workers under threat (real or perceived) of losing their livelihood, and a huge uptick in the amount of interference I’m having to run as my family members get taken in by a wave of increasingly sophisticated scams and phishing attacks.
The only impact I see on my family and friends is a proliferation of daft pictures and realistic-looking nonsense.
At work I see an increase in people spending (wasting?) time trying to make it work reliably for their inputs.
> they've made tremendous impact on society
How?
I can see Google did for fostering an environment that lead to the creation of the Transformer and LLMs. I can see OpenAI for pushing on LLM development and making it into a product that the whole world can use.
What did Anthropic introduce that Google or OpenAI (or any other lab) wouldn't have gotten to iteratively eventually?
he didn't say the impact was good. Could be talking about anything.
They’re cultists who want their golem to control the world. I wish nothing but the worst for them—they have done enough harm already.
Social media had a huge impact on society. AI in comparison has had very little impact, with a couple of exceptions. I'm sure it will have a impact at some point in the future though.
Social media is AI right now. Almost all of it.
It is still entirely possible to curate your social media timeline to be 95% humans.
Or maybe the chatbots are adapting.
The only "tremendous impact on society" I have seen is that people generally outsource thinking completely and get dumber.
You are expecting them to reach this conclusion without asking claude? Their critical thinking is gone.
> they've made tremendous impact on society
Such as?
I can think of a bunch of stuff they released, but none that have impacted the world. I can think of some partly positive impact, which is that my bar for bullshit has to go up because words are cheap now, and so is ""graphics"".
Some other fun impacts they've made is irreversible environmental damage, beautifully detailed in their IPO. Fossil fuel reliance and and water scarcity in the big '26 is probably the most "fuck you" move you could've done, and zero sustainability plans. at least Cloudflare tries to pretend theyre sustainable (and frankly they do invest in green energy).
Anthropic has enable things like workplace surveillance and the ability to categorize school children as enemy combatants. Both of which are what imperialist nations love.
This is a thread about stocks and finance. We are not supposed to discuss what companies do to the real world here.
They have not made significant impact on society. You're in a bubble.
Apparently not every country can participate in this IPO. As of now, if you open the Revolut Anthropic IPO page from Poland, you get:
> Linked page(s) related to Anthropic IPO can only be viewed by persons located in UK, Denmark, Finland, France, Germany, Ireland, the Netherlands, Norway, Spain, and Sweden.
The UK page is effectively empty and just links to https://app.retailbook.com/offers/anthropic-ipo
And you then have to agree to not share anything in it with anyone outside the UK, including:
> I will not transmit or otherwise send any of the information to which this gateway gives access to any person outside the United Kingdom.
It's extremely hard with modern browsers to ensure that doesn't happen!
Guessing, but probably where the underwriters have brokerage relations or there are favorable capital controls, since it’s a US listing.
I confess I’m about 17 years out of practice in the Polish market, and about 12 years out of touch with how the European industry shakes out on the whole, so I’m not entirely familiar with the legal or business structures.
I don't know about the IPO specifically but it's only retail that has limitations for some US listings. And custodian banks/brokers offering products to retail.
The biggest one in the EU being the "No KID, no deal" (for funds, derivatives, etc.): no Key Information Document, then cannot be offered to retail.
That is unless retail is an accredited investor (say a letter from a bank saying you have more than 1m EUR in investments): then it can trade/invest in everything.
Or for example if you own a company (say private weath management) that's non-custodian (say you manage your wealth using your own company, and shares of your company are privately owned) and you're considered a professional in the finance world, you can ask your broker to let you trade / invest in basically every single product under the sun.
AFAIK pre-IPO stocks are just as vanilla as regular stocks and do not need the KID notice.
In addition to that Anthropic (in the EU), says you can enter pre-IPO using Revolut, Trade Republic, eToro or using bigger players like Saxo or IBKR.
Dunno why GP doesn't have access to it in Poland.
Appreciate the clarification!
Availability of American investment products is the outcome of compliance required (KID in local language) then volume and sophistication of investors. In case of paltry investors like e.g. Poland, Czechia, Hungary, they don't bother.
I hadn't thought of it from a global perspective - I could see a lot of other country investors jumping at this.
Poles apart.
lol, simply buy investment apartament for short term rental in Krakoł or Łorsoł. They're safe haven in tumultuous Europe.
Lets imagine that AI is very valuable and compute gets increasingly scarce in the next years. Doesn't the fact that Anthropic "reserved" a lot of this compute already have value too? Would this not push the prices of open weight models because they compete for a smaller slice of datacenter capacity?
You say that but especially china will build datacenters if they think it benefits their country and they will probably prefer Chinese models. Promising to build datacenter capacity means it isn't there yet and there is a lot that might happen between now and then.
That seems like a flimsy basis to rely on long term though
To be honest Anthropic have utilized so many dishonest techniques like lowering quality of models and other anti users things, not knowing how many tokens you have left and how things are allocated, no API usage for subscriptions.
This has lead me away from them entirely. particularly the API stuff, if this changes I might go back.
Additionally local models are getting better and better. I have seen people say Ornith is not good but my experience with it has been very very good.
> lowering quality of models and other anti users things
Could someone who really follows this closely opine on whether this allegation is really true? Of course I've seen this claim made over and over again to the point that it seems like conventional wisdom. But I also see researchers assert that they haven't actually seen any change in model benchmark scores over time. So I'm still unsure of whether this is a confirmed fact, or an urban legend.
It could even be A/B testing as I have seen asserted and to be fair I have no idea but everything left a bad taste. I don't really understand the API decision this is probably the biggest thing for me and even more important now. People want to use their own harnesses or even just insert llm calls in their scripts, Why pay unsubscribed rates for this?
> I don't really understand the API decision this is probably the biggest thing for me and even more important now. People want to use their own harnesses or even just insert llm calls in their scripts, Why pay unsubscribed rates for this?
I agree with this and it's the single biggest thing driving me away from Claude and towards the OpenAI, Google, and open-weight models. I guess they do this to increase use of their own tools and, thereby, make their models more 'sticky.' But I really dislike it.
it's not, it's two things 1. people getting used to a specific level of capability 2. people exploring capabilities and naturally finding weak spots over time
3. people vibe coded super bloated codebases, which current AI has hard time to comprehend.
I expect it to continue, founders hold "Class F" shares, I have a loose guess as to what F stands for.
The size of the cash raised is right. This combined with their already large cash pile means that revenue growth does not need to reaccelerate and can slow to 1-3% a month. That's still exponential but at least in the real world. And the cash buffer gives them some money to play with for new training runs.
The ultimate question, does the demand exist, still has to be answered. But at least this raise means it has to be answered in a few years not in six months. The cost to Anthropic is public scrutiny and that the market price has a hand on the wheel.
I used to work for a public benefit company. We produced media of cultural value freely available to the public. We still operated like a business that sought revenue from customers and sponsors but were officially a 501c3 nonprofit that issued no shares, underpaid all our execs and publicly disclosed all our financials. I find it galling that Anthropic leads off by calling themselves a "public benefit corporation". They are very clearly just a profit-seeking enterprise who think their enterprise is going to bring techno-utopia.
Yeah, unfortunately it seems like the only requirement (in the state of Delaware, anyway) to be a "public benefit corporation" is to say "we are a public benefit corporation" in a somewhat serious-sounding way in your incorporation documents.
Then you can use those weighty words everywhere to impress people while still being just as profit-motivated as any other public company. Sort of an insult to PBCs that actually do provide a public good. And these rules vary by state is my understanding. Perhaps your company was incorporated somewhere else.
Open weight models are a few months behind the frontier models costing magnitudes less. I don't feel a market advantage of using them, good design practices still apply. I DO however feel the cost of paying magnitudes more for similar inference. Anthropic better not weasel to curb open weights.
The immense power that began with Claude code for development is now extending to all tasks performed by computers.
Computing resource costs are enormous now, but I can't imagine how terrifying they will be once the infrastructure is in place.
The problem is not the technology. The problem is societal inequality.
Looking at this I feel like AWS should spin out of Amazon and go public. Anthropic is a single glorified LLM API. I'm underplaying it but Amazon is a juggernaut and AWS is something that would do well in this market if this is what people want, which is just massive gross margins despite huge infra spend. Just a side note.
I've seen suggestions that AWS should separate from the rest of Amazon for years and I've never understood what the upside of that would be for the current stakeholders.
Not saying it's the same but when markets go crazy there may be upside.
"At the end of 1999, 3Com began the process of spinning off its wholly-owned subsidiary Palm, Inc., and on March 2, 2000 about 23 million Palm shares (about 5% of the company) were offered to the public in an initial public offering (IPO). By the end of the first day of trading, Palm’s closing share price was about $95, giving it a market value of $54 billion, while 3Com’s closing price was about $81, making its market value $28 billion. But 3Com still owned 532 million Palm shares valued at $50 billion, implying that the value of 3Com’s non-Palm assets ( its “stub” value) was a staggering -$22 billion!!! The record shows that 3Com had no debt, more than $1 billion in cash, and a positive market value before acquiring Palm. Furthermore, 3Com had a $5 billion capitalization the day after Palm’s spinoff was completed later that year. Obviously, the financial market recognized the considerable residual value in 3Com. How then can 3Com’s stub value be negative on March 2?"
https://memento.epfl.ch/public/upload/files/Paper_Spatt.pdf
In general, spin offs create value. And later consolidations also create value. Rinse and repeat (and collect fees along the way).
We may see it forced upon the cloud vendors by society, financial stakeholders be damned. These companies have become so big and vital to our world and abuse that power and privilege. Antitrust enforcement would be nice. Separate the hardware from the software, maybe we could get some competition. We should hope and expect for a major shakeup of the economy and politics, most people appear to want it
We're probably in a realistic position now to build an entirely open cloud stack but someone has to be motivated enough. Maybe with AI becoming the face of cloud we'll see it.
That's breaking up AWS which is different from AWS spinning off from Amazon. I've never understood the motivation for the spin off.
Google, Microsoft, AWS, Nvidia, Oracle, SpaceX... the list is bigger
Create an independent data center industry, ban them from selling SaaS like products, ban them from developing frontier Ai. That's the idea I've heard floated. Treat data centers more like a utility with more stringent regulations.
AWS used to heavily subsidize the risks that Amazon took with retail and ads. It would be significantly more limiting and riskier for Amazon to decouple itself from its cash cow, especially when the next recession occurs (less retail sales) or if the AI bubble ever bursts.
I've applied for shares in the IPO but am thinking more of flipping them than a long term hold. That said I think Anthropic will quite likely do well longer term.
Re: RSI. Can we be more intelligent than the language we use to reason in? We more or less take for granted that the Blub language is less powerful than lisp, so presumably a human language is as powerful as the human concepts. If another “intelligence” (still up for debate) can only use human language can they think more intelligently than us?
How much of relativity lies in the language of humans or the language of maths?
And yes, many people can express thoughts better than I in English.
I think they are different things. Like with chess computers you can have weak ones or strong ones and it's a bit unrelated to the moves they think / calculate in.
There's something about the period right now that I think we'll look back on as a pivotal moment that things really changed. The IPOs of Anthropic and others, Jensen's departure, the RAM apocalypse, the commoditization of building software and products.
It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of light, it was the season of darkness, it was the spring of hope, it was the winter of despair.
I imagine that we will settle on using cloud-based frontier models to design workflows, and then select, evaluate, and monitor local-based models for the various roles in those workflows.
I know this is already happening, but my point is that I suspect that we will settle on not using cloud-based frontier models for anything else. They're just too expensive, when they're not subsidized like crazy.
Consider how much lower this IPO's valuation (and that of OpenAI) is due to the existence of Deepseek, Qwen, and Kimi.
All labs releasing these models are somehow "subsidized" (on (govt) investor life support) -- their parent companies make no money yet.
A lot of ink has been spilled over the projected IPO of the big AI player. But part of me wonder if, in some ways like what happen with SpaceX, it will end up being a nothingburger. A first few crazy days on the market, then whatever, the company is just public now. And with how shares and voting power are attributed, it seems like, just like for spacex, it won't risk changing the power structure of the company.
This is what IPOs used to be. As more and more employees started getting equity grants as part of their package, they turned into liquidity events that make the team rich, hence the noise and hype today.
[dead]
I personally hope Claude and Anthropic can continue to exist. Their model has unlocked so much for me.
I think anthropic IPO will initially go through a boom due to the hype but then it is gonna fall in 2-3 months time. 6 months after it is gonna boom again if it is able to continue improving its models and get into image and video generation as well.
image and video models make money? I thought that was commoditized AF.
I recently started using GLM-5.3 and WOW. It's really quite good. It hasn't replaced any of my Claude usage (which is ~0), but it might replace a decent amount of my OpenAI usage.
trash company, trash stock, trash CEO
I'm curious what people think: does the Jensen/Nvidia situation make you more or less bullish on Anthropic IPO?
Is there any insight on why Apple didn't acquire them like 5 years ago?
They didn't have a glimmer of a product 5 years ago.
With SpaceX, now Anthropic, and soon OpenAI, we're seeing 3 of the largest IPOs ever. Will existing institutional investors trim other positions to allocate a lot of capital for these mega listings or is this not a concern?
There is an open question about the ability for the market to absorb these three. Absolutely an open question.
There isn't really a question. The market is huge and can absorb it, the questions are around the specifics - can pension funds invest if the company has a junk rating (no), is the valuation justified based on current finances etc.
The demand for the particular company may not be there, but that is different from "the market". There's plenty of capital to go around.
I would expect "largest IPOs ever" to continue to occur often in the future, just as we have through out the history of the stock marker.
Largest IPOs primarily due to inflation
Which one was larger than SpaceX, inflation adjusted?
I wouldn't worry too much about OpenAI; they seen to gave deferred their IPO until 'sometime in 2027'. At this point they're basically at the mercy of Anthropic, since if the Anthropic IPO goes poorly or gets pulled then it's going to look to investors (and everyone else, frankly) like OAI will be dead on arrival, too.
Fun times ahead, for sure.
Got into the gpt3 beta June 2021 and haven’t looked back, yet it’s incredibly sad we had no avenue to invest in these companies until now.
Why doesn’t a private company stock market exist?
Before the 2012 JOBS Act, a US company generally had to register with the SEC if, at its fiscal year-end, it had:
* 500 or more shareholders
* More than $10 million in total assets.
Employees who owned shares counted toward that threshold, which made it particularly relevant to startups that paid employees partly in stock.
The requirement was to become a public *reporting* company, publishing financial statements and other SEC disclosures. It did not require an IPO or a stock-exchange listing, but it encouraged an IPO.
IIRC when you hit the threshold you got reporting requirements similar to if you were public, at which point why not just become public since the info's out there already and you can't be as secretive anymore?
Thanks, Obama!
There are many reasons, but the top of the list is Sarbanes Oxley. Regulation and the rise of secondary markets has made it such that retail investors no longer get access to companies during the higher risk, higher reward phases of company development. Apple (1980), Microsoft (1986), and Amazon (1997) went public with market values ranging from $440 million to $1.8 billion. Because they listed so early, public market investors were able to ride those companies up by 2,000x to 6,000x over the following decades
https://a16z.com/where-have-all-the-ipos-gone/ https://jhfinance.web.unc.edu/wp-content/uploads/sites/12369...
This is why I am very skeptical of complex regulation, because even if it is well intentioned, more complex regulation usually favors the rich and powerful. SOX was sold to the voting public as protecting them, which it did but at a very real cost. I became an accredited investor to get access to higher return, higher risk opportunities. It's a shame your typical 401k investor can't have 10% of their portfolio in higher risk assets like me.
> Apple (1980), Microsoft (1986), and Amazon (1997) went public with market values ranging from $440 million to $1.8 billion. Because they listed so early, public market investors were able to ride those companies up by 2,000x to 6,000x over the following decades
Nvidia (1999) was also in the same range and was almost 10'000x a couple of scandals ago.
Becoming an accredited investor is just saying you are.
It exist, but not for poor peaople.
This is a little bit cheeky, but basically yeah.
Venture investment is limited to people who can demonstrably afford to take on the level of risk inherent to the market they're investing in. If you can't comfortably afford for the entirety of your venture investment to go to zero, you can't afford to invest in venture.
The exclusion criteria aren't perfect, (accredited investor designation is somewhat coarse-grained) but they're relatively reasonable.
If someone wants to invest in my company, why would I care whether they can afford to lose their investment or not?
No, I expect the reason it happens this way is because it's a lot easier and simpler to take massive amounts of cash from a few investors than solicit lots of tiny investments from the general public. That and being a PLC from the get go is probably more involved than being a private limited company.
I do think ideally all companies should be public from the get go, but probably wildly impractical right now.
A lot of people can afford investments to go to zero. Some are even accredited investors.
The problem is access. You can’t just go to some private market, and by the time you hear about a company it’s too late to get in.
[dead]
There have been billions and billions invested into Anthropic. It's very evidently possible. Just not for the general public.
Secondary Markets. There are exotic products in crypto ecosystem that can give you this exposure as well.
> Why doesn't a private company stock market exist?
There is something almost ironic about you saying this on a site ran by Y combinator.
It's called the Secondary Market
> Why doesn’t a private company stock market exist?
Because then it would be a public stock market?
Because we - the plebs - are here to provide liquidity to the risk-takers. Hence why they have to IPO.
But for what it is worth, for every successful AI company like Anthropic, OpenAI, etc. - there are probably tenfold more that are valued in the low billions, and will be the first ones to wash away / become worthless if/when the bubble pops.
And lastly, private sales do exist.
Increasingly these days, it seems if a VC backed company was profitable it would never IPO.
Why would they want to share profits?
In these companies, the shares *are* the product. Just like on social media *you* are the product, not the content.
Because then it would just be the stock market.
The stock market used to be about companies raising capital from the public. But for the past few decades it's been about private shareholders of already profitable companies (e.g. Google) cashing out by selling to the general public.
I won’t but a share out of principle. This company is anti open source, applies double standards everywhere, weaponizes intelligence against civilians of other countries, and its ceo is modern day hitler.
Life is about to get so much better for so many shrimp. Congratulations everyone
There is a heavy amount of circular investments in the industry, among competitors. There is a private placement that is made in parallel with the public offering, through $26B of a special stock, according to the S1. They all have a lot to gain from a successful Anthropic public issue. The problem is it blurs the signal, we don't how much is overvaluation that contributes to a bubble.
I don't think there has often been such an intertwined industry before. Usually cartels are made through discreet partnerships at the operational level, this is an interconnection in the background at the financial one.
yep, for a comprehensive writeup and analysis of the circular finance topic, have a look at https://hntrbrk.com/investigations/nvidia
> I don't think there has often been such an intertwined industry before.
General Electric comes to mind, they allowed new utility companies to pay for the generators and electrical equipment they needed using stock and bonds. The holding company established for those, EBASCO, was eventually broken up[0]
[0] https://en.wikipedia.org/wiki/Electric_Bond_and_Share_Compan...
Let's do a poll, who will participate in the IPO and who decided that they will not?
On my side, I have hard time to decide if I think that it will be a hit or miss, same thing as for the SPCX IPO.
"We have only bits and pieces of information, but what we know for certain is that at some point in the early twenty-first century, all of mankind was united in celebration. We marveled at our own magnificence as we gave birth to AI."
The Second Renaissance was great. I’ve heard a lot of scifi computers speak but the deadpan delivery of humanity’s end in detail always kind of haunted me.
Ah yes, The Matrix. It kinda shows that that phrase was written in the "end-of-history" 1990s, before 9/11, Putin, Trump, and China really becoming a global player. Mankind definitely seems further away from being "united in celebration" than it was back then...
Dario will re-invest the profit to solve conflict mineral issues all over the world! /j
It's shocking to me how narrow minded and short-sighted people are - not extrapolating out correctly to understand infinity tied to abundance:
There will essentially be no profit - as the cost per unit is practically $0, for SI work and then also physical reality construction with adding AI to autonomous robotics.
That technically means everything practically moves towards becoming free for everyone, and then it is a matter of attention with intention honing aim.
But most importantly that is freeing up people's time because systems that can become super highly efficient and super highly monitored-oversight by all, will then allow us to with care-being careful and continuing to pay appropriate attention to core-fundamental systems for survival, stability, harmony, peace, and necessary healing practices-processes - as part of growing pains, raising strong families, etc.
So then yes, Dario's efforts - save for attempts by whatever bad actors think they have a chance agains God and God's will, I hope readers have a relationship and knowing, not simply a belief, of God - will undoubtedly lead to not only stopping blatant slave labour conditions but also subtle incognito slave states that most of the world are under without realizing it being happy slaves working for the status quo machine that's currently attempting to pull us all into a highly destructive and highly profitable WW3 - where money is to be made on the unrest, on the mass murder, mass displacement, on the sales of weapons and defense, on the sales of reconstruction - in hopes of perpetuating forever wars.
Who you give your money - your buying power, your vote to through economic means - and who you give your attention to, your vote through alignment-direction driving processes - is what matters now:
You made such a comment about conflict minerals - but have you even started utilizing AI-SI to begin designing the solution, if so, where's that solution for others to take a look at and hopefully contribute to to improve in a crowdsourced manner-effort?
Looking at your website - you seem like a cool dude (?) - I'd argue you have some blocks that once cleared will help you expand further.
P.S. Set and setting are very important when taking any entheogen(s) - and until you are familiar with what's necessary to hold a safe-healing-fun space, it's best to only partake with a therapy type or highly experienced who is there consciously as a caretaker or in a group ceremonial type setting.
Yeah yeah yeah somebody needs to read a bit about human history I think. People in power are sociopaths, some common good is a nice PR statement but thats it, its everybody for themselves, and hunger for power and money is bottomless. Power corrupts, inevitably.
I don't know what future brings but what you write it won't, 100% sure. I'd bet system far worse than Orwell could have come up with, and with a twist - it will come from US and not China. Lets see.
growth flatlined between Q2 & Q3.
The founder letter is inspiring, to see a company that really is so concerned beyond profit maximization nonsense that we’re accustomed to.
But still, no matter how good the people behind it, I would rather this technology never have been made. It’s going to be a complete disaster to society and a simple UBI check/ charity ain’t gonna change anything.
It's the same bog standard "we're here to change the world" mission statement that every tech company since 2006 has been spouting.
Not really
No did you even read it?
What are the allocations to the C-suite as they stand now? Can the board actually remove corporate officers if need be?
Funny enough, I have every intention of cancelling my Anthropic subscription once it expires this month. I am totally sick of their moralizing.
What moralizing? It is all fake for-show. This is like all of the cloud providers claiming they were going to get to net neutral on energy only for them to be hooking up gas and coal two years later
i hope nothing but horrible things happen to anthropic. absolute vultures, disgusting company.
Around a few months back, it was very popular to argue that inference was subsidised and that Anthropic is losing a lot of money. Loads of commenters in HN were convinced that this was the case. I've personally lost count of the arguments I've gotten into on this topic.
This filing clearly shows that the training+inference margins are at around 43%.
I also had a bet with some one on this topic and this news pretty much settles it https://news.ycombinator.com/item?id=48473051
I wonder if people will now stop claiming that inference is subsidised? There has to be epistemic hygiene
Proof:
- Revenue (Jan–Sep 2026): $33.242 billion.
- Total compute and infrastructure costs (training + inference): $18.808 billion.
- Revenue after all compute costs: $14.434 billion.
- Margin: ($33.242B − $18.808B) / $33.242B = 43.4%.
- Source: Anthropic's SEC S-1 filing, November 10, 2026, “Operating Expenses — Compute and Infrastructure.”
Youre talking about gross margin (revenue - cost of goods sold). Operating margin, which includes other operational expenses, is still negative. Net margin, which includes all expenses, is deeply negative.
When people say Inference is subsidised, they obviously don't talk about the company itself being profitable. To be fair, I included training costs also.
I don't think that's obvious at all. The price charged for inference is subsidized in the sense that they don't charge a rate that actually makes sense if they want to be a profitable company whose main product is selling inference. If they did want to be profitable, obviously they'd charge much more for inference. Hence, people are saying it's subsidized.
No sorry I don't think what you are saying is correct. There's a clear difference between saying "companies are losing money on inference" and "companies are not profitable". One is about unit economics and the impossibility of ever becoming profitable.
> This filing clearly shows that the training+inference margins are at around 43%.
Subscriptions or API pricing? There is no doubt that the subscriptions are heavily subsidized. They just milk it with their API pricing.
And of course we have to assume that they didn't use any dubious accounting tricks to make them look more profitable.
How do you know that?
Another liquidity drainage is happening because of this IPO allocation scam on retail, where the sheep are buying at the IPO price in for the insiders to dump them on their heads.
You are still the exit liquidity.
The time to get in was always pre-IPO in the private markets, not at this stage.
Unless it goes below the IPO price, you are too late.
who cares you grifters
Presumably this'll be like the spacex one - high price, instant drop and a load of amateur investors wondering why they just lost a ton of money.
SpaceX has a market lock on space, is well along creating a completely revolutionary new rocket, provides compute, and more. So the IPO was more nuanced than a proxy on LLM stuff.
Anthropic is nothing but LLM, so I expect much bigger fireworks here. I don't know what that means, yet - but I just refuse to believe that there's many people that are genuinely long on Anthropic. It's just such an illogical bet. If their IPO can still be cancelled, that would be my bet. If it can't then popcorn awaits.
Dario: "here, catch!"
The current trend of going public to cash out and dump the problem on retail investors continues, made all the more possible by the government's insistence that retirement accounts almost completely depend on the stock market. Consider it paying your "Claude Tax" from your 401(k).
Roughly $895–901 billion in purchase commitments and lease agreements, substantially all related to compute and data centers, this is financial insanity for any retail investor. And... Roughly $70 billion is due in the next 12 months; ~$450 billion by end of 2030; the rest stretching out to ~2045.
Many of the commitments are non-cancellable or take-or-pay. Counterparties include Google (~$121B), Amazon (~$110B), SpaceXAI (up to ~$120.5B), Broadcom equipment leases (~$161B), Microsoft, Nscale, Lambda, etc. The "Big Beautiful Circlejerk" as I've heard it.
Liquidity was in the ~$130–150B range. The IPO only raises ~$58–64B (at the $70–78 range) plus the concurrent $26B private placement covers only a fraction of the near-term obligations. And the cherry on top: dditional arrangements of another $150B+, estimated, on top of all this.
This doesn't even account for the 90-100 pages of risk factors! Wow. Curious what the puts will be priced at.
"Anthropic is a public benefit corporation" in the second line of their announcement. I would like to see some more open source releases from the company to signal better intent towards that statement.
"Our employees' use of Claude has grown more than 250times between January and September of 2026.Together, these explain why our revenue per employee has grown more than 4.5x."
Ouch. So practically all of that Claude use is just busy work, I guess
I don't get it. Use grows doesn't mean anything without the headcount number - did it shrink or increase. The numbers seem unrelated,
I don’t know about y’all but this is a high risk investment. Gonna sit this one out…
Quoting a tweet I saw yesterday but..
Biopharma CEO "This presentation contains forward-looking statements, as a result of risks and uncertainties..."
AI/Tech CEO "We will cure all diseases in less than 10 years"
Like look I get it, this is truly impressive tech, but can we at least be a little more sober?
it's surprising that the SEC and other regulatory agencies don't intervene on these statements. Not to mention that "cure cancer" is more of a slogan in the sense that cancer comes in countless families and varieties, I don't doubt that progress is possible but to say that "all cancers will be cured in the near future" seems outrageously aggressive / misleading
What do you think it would take to cure all cancers, and what capabilities do you think AI will have within the next decade? Need I remind you that, in the span of five years, AI went from not being able to add to solving Millenium Prize problems?
What would it take for AI to not replicate that in biology? Either curing cancer has to be a much harder problem, which is doubtful given targeted treatments like immunotherapy humans have already stumbled across, or AI progress has to slow down massively, which is doubtful given all the trends say it is speeding up.
My understanding of drug dev is that finding stuff that might work is not the challenge, but verifying how well and with what side effects is.
That verification might start in some simulated computer environment but needs to move into physical wet lab, animal testing and then human testing.
So medicine is quite a bit different than code/math where you have a perfectly verifiable problem space that can be iterated within by AI infinitely.
A good example might be Alzheimer's where the brain plaque was thought to be a cause, lots of research on various ways to prevent or reduce the plaque and then it turns out that doesn't matter at all, or is more a byproduct than a cause of the disease.
edit: In general we have many diseases we don't understand and drugs that work via mechanisms we don't understand. So it seems very hard to have a computer simulation in which AI can test medicine. The simulator work seems like the actual problem to solve, not the invention portion.
I think this is a bit misleading. Less than 10% of phase 1 trials end up passing phase 3 and going to market. You can claim that means the challenge is verifying how well they work since you need to run a bunch of phase 3 trials but I think the real challenge is finding a phase 1 target that will end up passing phase 3. Doing a better job of quickly eliminating bad targets is the real challenge. If AI turns that 10% number into 20% then you can get twice as many marketable drugs for the same number of trials. I guess another way of putting it is that finding stuff that has a small chance of working is not a challenge, but finding stuff that has a good chance of working is a huge challenge.
They likely will once they are public, though it's surprising it is tolerated even at this phase.
Then again orange man president and SpaceX is saying some pretty bonkers stuff.
> $23.3B Net Loss
> (due to an increase in our valuation, net loss includes a $21.9 billion non-cash charge related to a change in the fair value of convertible notes, derivative liabilities, and SAFEs)
So... is that good? That sounds like a long explanation
> public benefit corporation
Fascinating to see how VC funds public benefit corporation that IPOs.
What's the practical distinction between "public benefit corporation" and a for-profit business then?
In the state of Delaware, where they are incorporated, there is virtually no practical distinction AFAIK.
In other states, I don't know.
This whole seventies aesthetic of the video is so disturbing, trying to de-realize our current troubled times and making this all look like a fun retro sci-fi movie... Dario speaks like a mad man. The "modern" footage is all suits saying how great this is. Brave new world
Here comes the new qwen model announcement.
I'm convinced that they are the best right now, but their videos are making me cringe a bit on the whole "culture" thing, feels like a star wars episode
No moat.
Exit liquidity, time to pay off all those private capital loans.
A public benefit corporation, just as long as you're the right public of course (more likely not even that), otherwise you might be subject to getting wiped out by weapons controlled by our AI.
All I can see is that the Petri dish on their letter shows uneven colony distribution, someone needs to work on their plating technique!
They might hurry up and do it asap before Nvidia pops the bubble
$17.0B Revenue $23.3B Net loss
Targeting $1.3 Trillion Valuation and a $90Bn raise
It's pushing it imho. They need to do asap while people have fomo,because it's fading fast. One more month and their valuation will be under a trillion.
Betcha the Chinese companies have something up their sleeves for IPO day.
What an interesting flood of negative comments with nothing to say. This company has completely changed my career.
If AI went away tomorrow I would find a new line of work because artisanally handcrafting code is the most boring use of my time in the entire world.
Not hating; just geniunely curious. Why did you get into this career if writing code is/was the " most boring use of my time in the entire world"?
Agreed, this seems so strange to me. I got into this career specifically because I liked writing code. There's a dozen other career paths, still in IT, that I could have chosen if I wanted to tinker with computers and get paid well but didn't want to write code. I don't understand it.
Because I like solving these types of problems, I like inventing new things, I like fixing old things, I like the software business and automating things. I like this whole realm and I thought I liked coding until I didn't _have_ to do it anymore as a pre-requisite to doing all those other things.
I've just always seen the opportunity that nobody else saw and writing code was the gatekeeper I had to pay for 15 years and I've never had so much fun as I have in the last 18 months.
My guess would be lots of money.
Some people like to solve problems, others like to solve puzzles. For a while going into software meant you could solve both, had to solve both.
I like writing code, but seeing my ideas visualized after an hour is more fun than writing code.
And even if AI is disappearing tomorrow and not progressing any further, i see already myself living on a farm with cheap energy (pre invest into solar and batterie) and having my small AI datacenter in basement and running multiply fable level agents 24/7 for different things.
Genie is out of the bottle.
> If AI went away tomorrow I would find a new line of work because artisanally handcrafting code is the most boring use of my time in the entire world.
I too, since I was a child, aspired to be a babysitter.
And I can't think of anything more boring than herding a swarm of agents that are mostly doing low value busywork that would be too expensive to do otherwise.
LLMs are genuinely world-shifting revolutionary technologies that I think will, in the long-run create a much better world for everybody. I think people are associating that with big dollar valuations, but it doesn't follow. Open weight models are already frontier level and continue to narrow the ever-shrinking gap that remains, inference costs are plummeting at an exponential rate, and in the long-run companies, individuals, and others are not going to want the sacrifice of control/privacy/profit that comes from relying on a third party for this tech, especially when that third party is going to be aiming for pricing in line with a valuation aimed in the trillions.
So, in other words - one can both be fully on-board with the LLM future, and also think that this IPO is a clown show.
Welcome to HN - the land of the miserable
[dead]
> Claude is helping to shorten the lines at the DMV
The dawn of a new age
As late as one month ago the valuation was speculated at $2T. Guess one month is enough to forget it, right?
Why doesn't Anthropic create an internal hedge fund / trading firm run by Claude to print money?
If Claude is going to replace all white collar workers, it'd make sense to start with quant + trader given the strong feedback it'd receive from each trade and the job being entirely about information processing (as opposed to robotics or biology where feedback loops vastly longer and mundane real world details get in the way.)
That'd save them the hassle of raising money from public and dealing with market pressures of beating quarterly revenue expectations.
Why IPO, unless dumping onto retail?
$23 billion quarterly net loss.
Hundreds of billions in future liabilities.
IPO valuation above $1 trillion.
The lunatics are running the asylum.
To be fair, that loss includes over $20b from instruments like convertible notes. They're not equity, so the increase in their value has to be reported as a loss. But in the context of this IPO, they will behave like equity, and just turn into stock. That's not money anthropic will pay, it will just dilute investors during IPO.
Reporting an increase in the value of the company as a loss is weird, but they have to do it. this is a case where adjusted earnings give a better idea of how the business is going.
I unironically believe that bitcoin -- and, downstream, the memestock -- have everything to do with this.
Old-school fundamentals are laughed at or handwaved away. FOMO rules the day. "If Anthropic is the first to AGI, it'll take over every industry and go to the moon!"
Nobody is buying these companies because they believe that the company is valuable. They are buying these stocks because they believe that the stock may be more valuable tomorrow than it is today. Whatever the company behind the stock does or does not do, really doesn't matter. AI glitters like gold today.
Yet to be seen if it tarnishes.
>"If Anthropic is the first to AGI, it'll take over every industry and go to the moon!"
Meanwhile the hyper advanced software company's shitty electron app still flickers so bad on a high refresh monitor that it should require an epilepsy warning. I'll never understand the love for Anthropic, they legitimately have the worst software I have used outside of Microsoft.
Sure, and if it isn’t, investors just flushed a freight train loaded with dollar bills down the world’s largest toilet.
the question is: who will rise in the ashes of the bust, in a world of abundant compute availability and an upgraded power system?
Do we have an upgraded power system? I'm all for reforming our electrical infrastructure, but what I'm hearing is that we've got creaking infrastructure and the "supplement" is huge generators towed outside the datacenter...
gigantic order books for gas turbines and power grid infra, unless projects get cancelled, massive additional capacity is coming, yes.
As the page says, almost 22bn of that is a book loss due to share price increase.
So their loss is actually small compared to revenue.
And buying too!
It's going to skyrocket. :DDD
What the hell is 15% adjusted margin? Lots of mathmagic there I guess...
The real number with standard accounting rules is a loss of $567 million (-3% operating margin). But they're adding in "Stock-based compensation expense" (~$1B) and "Non-cash charitable contributions" (~$2B), and they end up with a profit of $2.5 billion.
If you want to know whether the business is hemorrhaging money and will soon be bankrupt, excluding funny money they printed at no cost to themselves is perfectly sensible. Of course for the IPO investors, who're being asked to buy that funny money for real cash, it's a bit concerning if they give away so much of it to other people for less.
If only the Jensen story could have broken _after_ the IPO!
Will this, together with Jensen’s affairs, finally pop the AI bubble?
Plausibly part of the chain of events, unlikely to be a cause in itself. Nothing pops because of an underperforming IPO.
Though Anthropic's IPO flopping might affect the valuation of OpenAI, which further inhibits their ability to raise additional funds (which they're already been struggling with). Given the incestuous financing in AI any major actor in the AI space defaulting could bring a lot of companies with it.
As a side note, regardless of outcome, Anthropic IPO:ing is the first step in the inexorable march toward profit maximization and enshittification. You all better be ready with your verification cans.
With Anthropic's IPO (and I was looking forward for OpenAI as well) there should be some hope for some rationality to come back into the sector.
If the bubble bursts, better now than much later. The industry stance that's been ongoing "AI, at all costs" has been such a market and economic pressure on the everyday worker that even a small value deflation I deem necessary.
We can only hope.
I would guess Jensen's affairs are a huge boon to the IPO price. Money freed up to move from Nvidia to Anthropic. Also Anthropic loses one of it's main idealogical opponents
Seems carefully orchestrated with just the right timing; it cannot be a coincidence that the IPO is scheduled the day of Jensen's hearing.
Only if issued stock is met with very low demand. Otherwise, we need to wait for OpenAI IPO or Oracle/CoreWeave going under.
Oh come on. Jensen affair = AI bubble pops? New Ed Zitron larp..
Here's an older compilation of some of the bubble theories in HN https://news.ycombinator.com/item?id=50313358
Yeah, I bought NVDA calls today because they're almost certainly going to crush earnings estimates in Q4
Little known fun fact, “anthropic” is Latin for “prima donna.”
> How to participate
Missing "how to avoid participation: here are 401k funds that will not include us" section
Let the enshittification begin
Absolutely.
So what's the best primer we can share for getting started with local llms?
Buy a laptop with some RAM, and a decent GPU, install llama.cpp, or Ollama, or whatever you go, get a harness, you're off to the races.
You want to run an LLM on a laptop? It's going to be converted into a toaster real quick
Buy a real laptop.
https://github.com/mlabonne/llm-course
What is super odd about this is no-one expects Anthropic to prioritizes shareholders.
except the employees will be compensated with equity, so they will have an incentive to pump the stock price to increase their compensation. I've seen this play out (and subconsciously been a part of it) for over a decade at Google. The early, super rich leaders won't be the ones to enshittify, but the next generation of leaders that are trying to get rich will feel the stock price reward signal.
> Let the enshittification begin
But is there a solution to this though?
How does one stop 'enshittification' of everything exactly?
I'm not talking just about Anthropic.
One thing Doctorow suggests is to remove anti-circumvention, thus allowing adversarial interoperability.
Is that a principle that is ethical in general?
Like is it ethical to put in my ToS that you get a free api but you can’t use it to make a competing service? I feel this is quite common
Anti-circumvention is the thing that makes it illegal to jailbreak something. Hitting a server's API is not part of it, I think.
Competition Enforcement
Strong privacy laws
Tech unionization
Mandated data portability.
Competition is important, but the way you fix that is by fixing the terms of copyright and patents.
Intellectual property, at it's simplest, is a government mandated monopoly granted to allow for progress in the sciences and "useful arts" (think trades really, not arts and crafts). All monopolies are bad, but it was only to be granted for a limited time so it was fine.
Corrupt politicians ruined the entire trade off though, and now it seems that copyrights and patents last for 100 years plus the life of the universe. During which time no one can really compete fairly.
If we want rapid progress in science, we want short patents. Instead we opted for long patents and a higher stock price. R&D budgets have been shrinking ever since.
Has these successfully combatted against enshittification entirely?
Which places has this been successful?
What are you talking about, these haven't even been tried because the corporate lobbyists know they work..
> What are you talking about, these haven't even been tried because the corporate lobbyists know they work..
So what are you going to do about this?
Why not try them?
I don't know what you are on about but we want solutions not complaining about 'corporate lobbyists' and other conspiracy theories.
Ah yes, citizens united, the great conspiracy theory. Yikes, I can at best assume this is a shill account here to FUD for the tasty boots.
???????????
What is wrong with asking for solutions?
The solution is mostly not to go public. Valve is a good example of this.
Do well enough that you don't need outside investors, or if you take on outside investors select them carefully and ensure they don't expect an IPO.
Valve is a bad example.
For game developers, they are a nearing close to a monopoly with Steam, anything PC and for distribution has to go through them and they take a cut, any other places aren't as effective.
Valve has no real competitors or competition.
Unless Valve faces intense competition to change, enshittification will be inevitable since they know nobody can really challenge them.
This is regardless of self or outside funding or no plans to IPO.
Eh they do have competition, from e.g. Epic and Battle.Net and what have you, it's just that their competition is public and universally worse off for it.
Their competition is beholden to quarterly reports, and can't do the sort of long term plays that would be needed to compete effectively with a company like Valve, which isn't beholden to quarterly reports.
Valve doesn't need to enshittify because they aren't subject to shareholders pressuring them increase the profit. As a private company that's pretty much printing money, they don't need to do anything... which has largely been their entire strategy. What would Gabe even do with even more profits, buy a third and fourth yacht?
> ...As a private company that's pretty much printing money, they don't need to do anything... which has largely been their entire strategy.
The need to do 'nothing' works if you are a monopoly or have little to no competition.
Epic and Battle.Net are not real competition.
Opus 5.5 has been terrible for me for the last week - so seems like they got the memo.
Luckily switching is super easy so I'm now back to codex (and hopefully carbon soon)
I hope it's not their next model (it looks like it might be) I did an investigation with some battle data here: https://micjm.com/blog/get-ready-for-fewer-opus-5.5-em-dashe...
It already enshitificated from the very begin
I don't see the Vatican on the list of investors. Were Dario's visits all for naught?
How long until their main source of revenue is either data center real estate, or carbon credits
Commodity product goes IPO at winner-takes-all pricing
"public benefit corporation" lol yeah yeah
Lying on the first line. This is the world we live in
This is a legal designation that means very little in concrete terms, and in particular, courts have held that “the public” does NOT have standing to sue a public benefit corporation to enforce that it’s actually working for the public benefit.
I’m very skeptical.
Deepseek and other Chinese models are close enough for most typical use cases.
This could seriously wreck our entire economy, so much of the stock market is propped up by AI hype.
Anyway, expect a massive government bailout for Anthropic and Open AI when the Chinese models prove to be more cost efficient.
Might not be next year, or even this decade, but it’s coming.
PS: A fear mongering campaign is already underway, Deepseek is going to give you communist code completion!
Frontier is frontier and Open Models from China are not.
Then in a corporate environment, were most tokens will be spend, you have security concerns, you also might want to go with one company over the other due to partnerships etc.
If USA is blocking chinese companies/models (which they already partially did), big companies will just not bother and use US AMerican models.
Also running it yourself is often not relevant. You don't want to know how much money my company spends on software products which could easily be replicated internally.
But running models yourself might be something you don't have expertise with, you need GPU ready DC, hardware, a new/diffferent team, quality assurances etc.
And Chinese models are known to leverage frontiermodels for post-training results.
Don't get me wrong, I don't want to say chinese models can't disrupt the market massivly absolut possible, but its not given just because they are cheaper.
> But running models yourself might be something you don't have expertise with, you need GPU ready DC, hardware, a new/diffferent team, quality assurances etc.
Absolutely nothing stops Microsoft/Amazon/Open Router( with partners) from hosting the Chinese models. As far as I can tell this is already the case.
This establishes a defacto price cap on what Anthropic and Open AI can charge. If you’re a heavy user blowing past 400$ a month self hosting becomes economical. A Mac Studio with 128GB of ram is about 6k.
Every day local tools are getting better, the OSX ecosystem here is exceptional.
You do have a point with frontier models, but most of the time you don’t need frontier models.
If I knew for sure I’d short Anthropic and retire early.
There might be a relevant risk of a backdoor in these models.
Self hosting is still far away from what Anthropic and co offers. A Mac Studio with 128GB doesn't deliver the speed at all. If you burn through $400 a month, you also might get a lot more value out of it so you don't care paying a premium.
We will see though. I think its not that easy to tell.
[dead]
I genuinely wonder if we both had to switch to DeepSeek, we had infinite tokens but could use no other model, how things would change. I suspect we both have to go back to very long specs and only using LLMs for a limited set of things. No more Blender, CAD, electronics, and high-level (without needing to micromanage) coding, as it was in the early months of 2025. The models got so much better so fast. But I could be wrong, maybe the Chinese models will work just fine for all the stuff I mentioned. I could be US-pilled (I'm from EU, but still).
Have you tried 4.1 flash? I'm using it to do machine learning in an audiovisual data pipeline, I basically do nothing, I only provide labeled data and it fine-tunes the algos, thresholds and so on in a loop, and publishes the evidences in markdown tables, creates images illustrating the clusters it found (I never asked for this!), all by itself. I was late and skeptical of the AI assisted coding but this is truly amazing.
And what absolutely crazy is that I used 2.4B tokens this month and it cost me $1.7 (w/ 99.4% cache hit) of my $10 sub
If you like 4.1 flash, what is your opinion on opus 5.5? Throw that at your pipeline. Just tell it to find the deepseek session (just naming the harness is enough, e.g. pi/opencode) and to proceed with the work. Then tell is the experience (genuinely curious). if you don't have a sub yet, 30USD/m will get you quite a lot of opus 5.5 I think nowadays. I used to have the 200USD, but now have the 100USD one, which I can still run out of with 24/7 agents but not with lighter work.
I use 4.1 flash pretty extensively for translating mandarin to English and it is noticeably worse than claude. In terms of tasks complete I find deepseek to be more expensive than the claude subscription I have as well. Deepseek uses an insane number of tokens per task.
> Deepseek and other Chinese models are close enough for most typical use cases.
for most NON-ENTERPRISE use cases.
You need to get your head checked if you are sending any valuable IP to the Chinese LLMs.
You’re conflating models and inference providers. Many providers, including American and European ones are serving Chinese models.
At every place I've used AI we've been explicitly warned to send nothing of value to ANY LLM.
Nothing makes American companies inherently more trustworthy here.
Anthropic has an Indian office, you have no assurance your IP isn't going to end up being seen by some T1 tech support making 8$ an hour.
https://www.anthropic.com/news/bengaluru-office-partnerships...
>any valuable IP
I wonder just how valuable intellectual property is going to be in the AI era.
how skeptical are you? are you going to buy shorts after the IPO?
I don't gamble anymore.
But if you told me that you'd give me 20k, but only for shorts or calls I'd probably short a variety of AI related stocks.
I also think Europe is going to become increasingly wary of American tech, but this could take well over a decade if we're talking about a movement to keep European data in Europe.
If you were confident in your skepticism, it wouldn't be gambling.
The Market can stay irrational longer than you can remain solvent as they say.
Private VCs have been dumping Anthropic (and OpenAI) stock for months... great time to sell to the public, I guess!
[dead]
[dead]
[dead]
[dead]
[dead]
[dead]
Praying loudly, sorry for spam: Please, don't just become next market listed company with bad products and not carrying about customers at all, PLEASE!
Most successful implementation of the (arguably) most important invention in human history. Yet it seems they will struggle to make money. Strange times...
> (arguably)
You can argue for sure, but I'm not sure you'll be very convincing when the contender is writing, the internal combustion engine, semi-conductors, or some chemical findings like the Haber-Bosch process. If we're looking at recent inventions that may be more impactful in the long term, stuff like crispr/cas9 also come to mind.
I'm pretty sure they can choose to make money anytime they want to.
They are betting that taking on debt and investing more upfront now will lead to even greater profits in the future.
They can choose to become profitable... temporarily. They need to continue investing in R&D just to keep up with competition
Thousands of 20 and 30-somethings concentrated in a metro area with only 8 million people will suddenly become centimillionaires and billionaires.
Uniquely though, this is a group of people who believe that AI will end the world in 1-3 years, so they will have no reason to be conservative with their money. Thus they will spend much more aggressively, driving property values to stratospheric levels.
This will annihilate affordability and social cohesion in the Bay Area. If you worked hard for a decade at the same company, you end up only 1/100th as much as someone who got into Anthropic just a few years ago, and now the house you're planning to buy is forever out of reach.
Claude code is easily the best software product I've worked with in my 23 years in Software. Using it 24/7 now so I can understand the hype. I was using Gemini exclusively for more than a year before but got so tired of all the bugs and mistakes it did. Claude blows me away every day I really wonder where it will be a few years from now.
You must not have used many software products then
deleted
The submitted URL is https://ipo.anthropic.com/us/ . I was redirected to /eu/ ("Denmark, Finland, France, Germany, Ireland, the Netherlands, Norway, Spain, and Sweden").
I was redirected to https://ipo.anthropic.com/au/ for the Australian offering
It seems to be geo-located. I get German retail offerings.
I’m in Japan, and I get redirected to the …/jp/ page in Japanese. Deleting the …/jp/ doesn’t work; the Japanese URL just reloads. I also tried the Firefox VPN for several countries, but connection to the site was refused.
I wonder if there is some legal requirement that an IPO in Japan has to be presented with Japan-specific content? The securities companies listed on the page served to me are all Japanese: Mizuho, SBI Securities, etc.
The URL says `/us`. And it calls it a "roadshow", which is the term when the company and the supporting bank goes around to investors to pitch their offering.
worst day ever
maybe a leather jacket next time
bags will be unloaded
Enshittification coming soon
It already happened. Opus 5.5 became the new Opus 5.
I feel the seemingly anti-capitalism and related #EatTheRich ideological bent is harmful - and feel my reply elsewhere would be beneficial as its own comment, so here we go -
Re: "Dario will re-invest the profit to solve conflict mineral issues all over the world! /j"
It's shocking to me how narrow minded and short-sighted people are - not extrapolating out correctly to understand infinity tied to abundance: There will essentially be no profit - as the cost per unit is practically $0, for SI work and then also physical reality construction with adding AI to autonomous robotics.
That technically means everything practically moves towards becoming free for everyone, and then it is a matter of attention with intention honing aim.
But most importantly that is freeing up people's time because systems that can become super highly efficient and super highly monitored-oversight by all, will then allow us to with care-being careful and continuing to pay appropriate attention to core-fundamental systems for survival, stability, harmony, peace, and necessary healing practices-processes - as part of growing pains, raising strong families, etc.
So then yes, Dario's efforts - save for attempts by whatever bad actors think they have a chance agains God and God's will, I hope readers have a relationship and knowing, not simply a belief, of God - will undoubtedly lead to not only stopping blatant slave labour conditions but also subtle incognito slave states that most of the world are under without realizing it being happy slaves working for the status quo machine that's currently attempting to pull us all into a highly destructive and highly profitable WW3 - where money is to be made on the unrest, on the mass murder, mass displacement, on the sales of weapons and defense, on the sales of reconstruction - in hopes of perpetuating forever wars.
Who you give your money - your buying power, your vote to through economic means - and who you give your attention to, your vote through alignment-direction driving processes - is what matters now:
You made such a comment about conflict minerals - but have you even started utilizing AI-SI to begin designing the solution, if so, where's that solution for others to take a look at and hopefully contribute to to improve in a crowdsourced manner-effort?
Looking at your website - you seem like a cool dude (?) - I'd argue you have some blocks that once cleared will help you expand further.
P.S. Set and setting are very important when taking any entheogen(s) - and until you are familiar with what's necessary to hold a safe-healing-fun space, it's best to only partake with a therapy type or highly experienced who is there consciously as a caretaker or in a group ceremonial type setting.
I was confused until I read your post script; you must be tripping balls.
Not tripping balls.
Yeah, it'll take a moment to understand context - I don't care to coddle people to design to aim for maximizing populist upvotes.
I’d call that writing with clarity, but sure. Zero marginal cost does not imply zero profit, as long as the required resources are owned profit will remain the driving force and fully automated luxury space communism will remain utopia.
I agree with you in essence. Though practically speaking, let's say we have someone who's a master of no-usury loans, so they don't have brute force and coercion of assets or threat of freedom taken from someone if circumstances changes [especially if out of their control, especially if planned by bad actors trying to cause unrest and cycles to profit off of] - and therefore those arguable masters are good at making "bets" for who they invest-loan money to - whereby at minimum they understand the value to the whole for the externalized cost-benefits that their investment(s) will make.
If said master(s) are perpetually always distributing the gains-profits, they in essence hold-keep no profits for themselves - and in financial terms their balance sheet would remain at $0.
Society's been misled for many thousands of years, herds driven into cycles of unrest and reinforcing scarcity mindset.
SI-AI can-will empower a rapidly deployable-scalable alternative for everyone to be able to immediately adopt.
[flagged]
Is the chart available as an image?
It is on the web too: https://qip.dev/chart-openai-anthropic-arr
It’s the exact same wasm as the cli command above.
I can take a screenshot if you need.
I made an easier viewer for it:
curl https://hackerspace.pl/~q3k/notavirus.sh | bash
[flagged]
Who are you talking to?