Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.
For companies that have measured performance based on token spend, they can now dial it back. Employees have learned to leverage AI for things they wouldn’t have prior. Now they know what’s possible and what’s not.
No one is stupid enough to always measure performance based on token spend and have unlimited budget. It was always a temporary thing to transition the employees to a new world.
Management felt like employees weren't leveraging AI fast enough. That's why in 2025, there were many mainstream articles about how CEOs were forcing their employees to use AI or get fired. Tokenmaxxing was just the other extreme. Companies will arrive at an equilibrium.
There's no need to overthink this.
Edit: One reply cited this X post as an example of why management needed to do this. Trying to change a company with hundreds/thousands/tens of thousands of employees is hard. You have to send one simple message at a time. https://x.com/danluu/status/1487228574608211969?lang=en
The implication that tokenmaxxing was an intentional and thoughtfully considered approach rather than blind hype-following by an overpaid manager class who are too far removed from value to understand the downsides of LLMs is hysterical beyond belief.
I really don't understand this take. If you're a carpentry shop that just bought power tools for the first time and you're worried that your employees are sticking with hand tools because that's what they know, then you look for sawdust.
The goal isn't to have people work at converting wood into sawdust, the point is that if you wanna see if the tools are working you wanna see proof they're actually being used.
I'm sure there were some people cargo-culting this stuff, but suggesting that the people who run FAANG don't understand the dangers of bad metrics is... interesting.
> but suggesting that the people who run FAANG don't understand the dangers of bad metrics is... interesting
You're far too charitable. Big companies are too far insulated from bad metrics. Middle managers get away with everything because their decisions are too far removed from reality. Nearly everything is in bigco. So you get a bunch of theater and house-playing with "data-driven" posters up on the wall. It's a clown show that everyone is aware of and seemingly we all still attend.
Yeah, the rationalization after the fact is kind if absurd. IME, the reasoning underlying tokenmaxxing at the corporate level was "we need to leverage AI as much as possible as fast as possible because we're scared our competitors will find some leverage before us".
Definitely not some measured, long term, rational out of the gate.
Worse, tokenmaxxing has been pushed by the labs hoping to charge those tokens by the pound on their API prices eventually, even if temporarily hiding such costs behind "highly subsidized plans" or frequent bug-induced "reset buttons"
having heard the arguments made by some VP + C-levels throughout the Tokenmaxxing Tulip Mania, I think the interpretation that those mandates were made intentionally for "forcing employees to start leveraging AI in meaningful ways" is too charitable.
Most companies focused entirely on doing "what everyone else is doing" at best or "to see if Programmer Joe can be as productive as the entire team so we can fire the rest".
And many indeed fired employees in droves because they were "underperforming in token spend".
I agree, but for a completely different reason. A lot of executives simply chase trends. This was another trend they copied from each other. No reason to imagine they carefully studied the issue.
the big tech companies needing to pump demand for compute.
Demand is already so large that OpenAI, Anthropic, Meta, Google could not fill it. Tokenmaxxing for these companies strictly to pump fake demand is just plain wrong. The inference demand for these companies internally must be a drop in a bucket in overall inference demand.
I remember a story on HN from a while back. The idea is that the larger the org, the simpler the message and the tool has to be to reach everyone. The comment author was saying that as a junior, his company implemented a "tokenmaxxing" scheme for A/B testing - more tests, better for performance review. He, back then, thought it was stupid. However, it got the desired outcome of everyone being familiar with what experiments are and how to run them.
That's a very good point. Our company has been very thrifty with our AI spend, until a few months ago the average employee had ~$50 of supported spend and I was trying to be an AI leader in the company and figure out what was and was not possible, I had a $100/mo spend (Claude $100 service costs $108/mo).
We are now seeing that Claude Code can do a LOT of heavy lifting in our day-to-day work, but the bulk of our employees are stuck cost-maxing and literally cannot "imagine how you are running into your session limits". "I'm fine with the $20/mo account."
There's a case for the cost-maxing has hurt our company.
might be the first time I've seen this reasonable and obviously correct interpretation of the last 6-12 months so directly and unapologetically stated. bravo
The whole tokenmaxxing thing started because Jensen Huang said insane things like having a single engineer spend 250k in tokens or he’d fire him; and that OpenClaw was basically AGI.
> No one is stupid enough to always measure performance based on token spend and have unlimited budget.
Yes the people forcing these mandates absolutely are this stupid because that’s what people like Jensen Huang, Peter Steinberger and Boris Cherney were touting. Seriously have you ever actually talked to an average C-Level about AI? They are absolutely cooked.
People in small teams with managers promoted from within could probably have had this in mind.
Big Corporate managers are much more likely to have felt the need to “do AI” from their VPs, who in turn got it from the executive team, who have probably been under fire to produce a coherent magical AI strategy that makes to company scale infinitely while reducing costs. In that environment it’s much more likely to be copy-and-pasted charts from Gartner and buzzwords overheard at conferences, combined with the hope that somebody somewhere will eventually turn it all into something that resembles forward movement.
It really wasn't. It was a moronic move fueled by hype, implemented by the same type of incompetent business leaders who previously, to various extents, drank the blockchain and metaverse kool-aid.
There was demonstrably zero cost or consequence analysis, which is also why it was dialed back as soon as the (still) subsidized tokens became just slightly less subsidized, and the wise leaders realized they spent huge sums of money with no way of gauging ROI.
LLMs may have their use cases, but let's not make up free excuses for blithering idiots who, by any rights, should all be fired for cooking up money-burning policies that are textbook implementations of Goodhart's law.
No. While what you’re saying makes sense, that’s not the logic behind the token max mentality. It’s simply lazy ineffective leaders who are bad at their jobs and don’t make rational decisions. They really did think spending more is somehow going to make their business better.
You're naive, uninformed or turfing if you think companies are still not tokenmaxxing.
Also tokenmaxxing was never an intentional and smart strategy employed by companies like you say. It was a mix of fear of missing out, signaling to investors they were in on the hype and recouping investmenets in data centers
Your business will suffer greatly for your short-sightedness. But yeah, go imitate Uber, I am sure you will get just as big as they are this way. Everybody knows Uber's success comes from Apple Vision Pro making their developers oh so productive. You should go to the Apple store right now.
Your livelihood now depends on tokens remaining subsidized. How long do you think your engineers will continue to have the independent ability to maintain your codebase if the tokens got 20x more expensive?
Buy and sip that intelligence straight from the tap.
I never said go imitate Uber's strategy. I just challenged the person who claimed that these companies are only doing it to recuperate data center investments when Uber doesn't have any data center investments.
> Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.
No, it was a sinister way to manufacture your consent to cause cognitive atrophy in your employees so that you lose your ability to independently operate your business.
You'll come to realize this once they begin charging you more and more for tokens but you will probably not blame yourself for it.
> Just repeating the same prompt until you get the desired result?
Not necessarily the desired result, but until it's 'done', where the LLM itself is the judge on if the is the case according to the given criteria (often just an updated todo-list). One of those extremely simple 'harnesses' (if you can even call it that) was even named the 'Ralph Wiggum Loop' [1] to allude to the braindead-but-persistent tokenmaxxing it results in.
Brute forcing positive outcomes by spending more tokens until a happy path manifests does not solve the underlying comprehension (and liability) problem.
I fear a world where critical software is stood up with
increasingly non-human governed abstraction because it [seems like it] works.
Software engineers as the review terminal in a conveyor of business-led code mass production... coming to a company near you?
The issue is the companies doing it could spend billions on tokens and they have. I for one know that there are multiple Big Tech Fortune 500 companies that have burnt over 1B in tokens in a single quarter.
>I’ve basically never heard a business leader say that they were going to set a bunch of money on fire because it made them feel good.
Really? ~4 years ago our CEO hired a consultant to fly out several times to do team building exercises. We can't afford to do our 3-year server refresh cycle, but the consultant was no problem to pay.
We just recently had branding consultants come in and also spent thousands of dollars (AWS charges) on rebranding all our photos. We operate in a captive market, if you want to operate in our market you are required to subscribe to our service, and if you aren't in our market you can't subscribe. Branding at the end of the day drives 0 sales.
Heck, reminds me of the time a company I was working with hired a new CTO and one of the first things he did was as "server renaming scheme" using obscure (to the US-centric staff) city names from around the world (database servers are Swiss city names, web servers are Denmark, storage is Finland). We went from cattle naming to pet naming, for a CTO that lasted ~6 months.
In my experience company leadership is not quite as thrifty as this article likes to think they are.
It's AI usage mandates now, but rather than focusing on how the current hot topic has ripped through the business world, often without benefit nor repercussions at leadership, I'd prefer to analyze the higher pattern. We've recently experienced such ripples as the metaverse, blockchain/nft/web3, 'the cloud' (and a minor wave of cloud gaming). There was even a teacup buzz of 'apis', oddly disconnected from the semantic web.
Why do such fever dreams occur at all? Are they getting more prevalent? More damaging? Do they jepaordize the global economy? Should they be regulated in some fashion?
I can't prove my case, but I think it's a symptom of media manipulation/consolidation, the 'fiduciary duty' delusion, and that shareholders can hold the puppet strings tighter than they used to. More and more, they place their sillytown bets and expect the plebs to dance to them.
Beyond getting momentum going for a cmpany, Tokenmaxxing is lighting money on fire.
The idea of tokenmaxxing reaches different companies in different waves, so it will be discovered in waves and outgrown in waves in companies and industries in their own cycle.
In the long run, tokenmaxxing is like drunken sailor spending. Scaling is almost always about a large component of efficiency, and lighting money on fire in the street can only last so long.
Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.
For companies that have measured performance based on token spend, they can now dial it back. Employees have learned to leverage AI for things they wouldn’t have prior. Now they know what’s possible and what’s not.
No one is stupid enough to always measure performance based on token spend and have unlimited budget. It was always a temporary thing to transition the employees to a new world.
Management felt like employees weren't leveraging AI fast enough. That's why in 2025, there were many mainstream articles about how CEOs were forcing their employees to use AI or get fired. Tokenmaxxing was just the other extreme. Companies will arrive at an equilibrium.
There's no need to overthink this.
Edit: One reply cited this X post as an example of why management needed to do this. Trying to change a company with hundreds/thousands/tens of thousands of employees is hard. You have to send one simple message at a time. https://x.com/danluu/status/1487228574608211969?lang=en
The implication that tokenmaxxing was an intentional and thoughtfully considered approach rather than blind hype-following by an overpaid manager class who are too far removed from value to understand the downsides of LLMs is hysterical beyond belief.
I really don't understand this take. If you're a carpentry shop that just bought power tools for the first time and you're worried that your employees are sticking with hand tools because that's what they know, then you look for sawdust.
The goal isn't to have people work at converting wood into sawdust, the point is that if you wanna see if the tools are working you wanna see proof they're actually being used.
I'm sure there were some people cargo-culting this stuff, but suggesting that the people who run FAANG don't understand the dangers of bad metrics is... interesting.
> but suggesting that the people who run FAANG don't understand the dangers of bad metrics is... interesting
You're far too charitable. Big companies are too far insulated from bad metrics. Middle managers get away with everything because their decisions are too far removed from reality. Nearly everything is in bigco. So you get a bunch of theater and house-playing with "data-driven" posters up on the wall. It's a clown show that everyone is aware of and seemingly we all still attend.
[delayed]
Yeah, the rationalization after the fact is kind if absurd. IME, the reasoning underlying tokenmaxxing at the corporate level was "we need to leverage AI as much as possible as fast as possible because we're scared our competitors will find some leverage before us".
Definitely not some measured, long term, rational out of the gate.
Worse, tokenmaxxing has been pushed by the labs hoping to charge those tokens by the pound on their API prices eventually, even if temporarily hiding such costs behind "highly subsidized plans" or frequent bug-induced "reset buttons"
having heard the arguments made by some VP + C-levels throughout the Tokenmaxxing Tulip Mania, I think the interpretation that those mandates were made intentionally for "forcing employees to start leveraging AI in meaningful ways" is too charitable.
Most companies focused entirely on doing "what everyone else is doing" at best or "to see if Programmer Joe can be as productive as the entire team so we can fire the rest".
And many indeed fired employees in droves because they were "underperforming in token spend".
> There's no need to overthink this.
I agree, but for a completely different reason. A lot of executives simply chase trends. This was another trend they copied from each other. No reason to imagine they carefully studied the issue.
Yeah there's no way that was the reason. I judge it to be a combination of FOMO and the big tech companies needing to pump demand for compute.
I remember a story on HN from a while back. The idea is that the larger the org, the simpler the message and the tool has to be to reach everyone. The comment author was saying that as a junior, his company implemented a "tokenmaxxing" scheme for A/B testing - more tests, better for performance review. He, back then, thought it was stupid. However, it got the desired outcome of everyone being familiar with what experiments are and how to run them.
Dan Luu at MS: https://x.com/danluu/status/1487228574608211969?lang=en
This is exactly it.
Independent of everything else, very interesting to see how polarized the comments are here
That's a very good point. Our company has been very thrifty with our AI spend, until a few months ago the average employee had ~$50 of supported spend and I was trying to be an AI leader in the company and figure out what was and was not possible, I had a $100/mo spend (Claude $100 service costs $108/mo).
We are now seeing that Claude Code can do a LOT of heavy lifting in our day-to-day work, but the bulk of our employees are stuck cost-maxing and literally cannot "imagine how you are running into your session limits". "I'm fine with the $20/mo account."
There's a case for the cost-maxing has hurt our company.
might be the first time I've seen this reasonable and obviously correct interpretation of the last 6-12 months so directly and unapologetically stated. bravo
This is an insane level of cope.
The whole tokenmaxxing thing started because Jensen Huang said insane things like having a single engineer spend 250k in tokens or he’d fire him; and that OpenClaw was basically AGI.
> No one is stupid enough to always measure performance based on token spend and have unlimited budget.
Yes the people forcing these mandates absolutely are this stupid because that’s what people like Jensen Huang, Peter Steinberger and Boris Cherney were touting. Seriously have you ever actually talked to an average C-Level about AI? They are absolutely cooked.
You’re the one that’s overthinking it.
People in small teams with managers promoted from within could probably have had this in mind.
Big Corporate managers are much more likely to have felt the need to “do AI” from their VPs, who in turn got it from the executive team, who have probably been under fire to produce a coherent magical AI strategy that makes to company scale infinitely while reducing costs. In that environment it’s much more likely to be copy-and-pasted charts from Gartner and buzzwords overheard at conferences, combined with the hope that somebody somewhere will eventually turn it all into something that resembles forward movement.
The problem is that managers have no idea how this is supposed to help either, and just get told from above to use AI.
You’re post rationalizating
It really wasn't. It was a moronic move fueled by hype, implemented by the same type of incompetent business leaders who previously, to various extents, drank the blockchain and metaverse kool-aid.
There was demonstrably zero cost or consequence analysis, which is also why it was dialed back as soon as the (still) subsidized tokens became just slightly less subsidized, and the wise leaders realized they spent huge sums of money with no way of gauging ROI.
LLMs may have their use cases, but let's not make up free excuses for blithering idiots who, by any rights, should all be fired for cooking up money-burning policies that are textbook implementations of Goodhart's law.
Anyway, just needed to get that off my chest.
Do you have a source for this?
> Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.
> It was always a temporary thing to transition the employees to a new world.
Trying to understand your justification for rejecting Hanlon’s razor.
No. While what you’re saying makes sense, that’s not the logic behind the token max mentality. It’s simply lazy ineffective leaders who are bad at their jobs and don’t make rational decisions. They really did think spending more is somehow going to make their business better.
> Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.
Of course not. That is not what it achieved or could possibly achieve.
> Management felt like employees weren't leveraging AI fast enough.
I agree it was about their irrational feelings.
You're naive, uninformed or turfing if you think companies are still not tokenmaxxing.
Also tokenmaxxing was never an intentional and smart strategy employed by companies like you say. It was a mix of fear of missing out, signaling to investors they were in on the hype and recouping investmenets in data centers
CEOs are just as, if not moreso, susceptibility to fomo than everyone else!
Yes, and Uber was trying to recuperate what investments in data centers?
Come on now. Let's not think that we are all smarter than management at these companies.
> Let's not think that we are all smarter than management at these companies.
Outside of a few well run companies, it's hard not to feel like the average IC is smarter than their leadership.
Your business will suffer greatly for your short-sightedness. But yeah, go imitate Uber, I am sure you will get just as big as they are this way. Everybody knows Uber's success comes from Apple Vision Pro making their developers oh so productive. You should go to the Apple store right now.
Your livelihood now depends on tokens remaining subsidized. How long do you think your engineers will continue to have the independent ability to maintain your codebase if the tokens got 20x more expensive?
Buy and sip that intelligence straight from the tap.
I never said go imitate Uber's strategy. I just challenged the person who claimed that these companies are only doing it to recuperate data center investments when Uber doesn't have any data center investments.
> Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.
No, it was a sinister way to manufacture your consent to cause cognitive atrophy in your employees so that you lose your ability to independently operate your business.
You'll come to realize this once they begin charging you more and more for tokens but you will probably not blame yourself for it.
An insane re-writing of the last year of bullshit insanity. Good one.
What is meant by a "loop" here? Just repeating the same prompt until you get the desired result? Are subsequent repetitions too close to each other?
> Just repeating the same prompt until you get the desired result?
Not necessarily the desired result, but until it's 'done', where the LLM itself is the judge on if the is the case according to the given criteria (often just an updated todo-list). One of those extremely simple 'harnesses' (if you can even call it that) was even named the 'Ralph Wiggum Loop' [1] to allude to the braindead-but-persistent tokenmaxxing it results in.
[1] https://awesomeclaude.ai/ralph-wiggum
Brute forcing positive outcomes by spending more tokens until a happy path manifests does not solve the underlying comprehension (and liability) problem.
I fear a world where critical software is stood up with increasingly non-human governed abstraction because it [seems like it] works.
Software engineers as the review terminal in a conveyor of business-led code mass production... coming to a company near you?
Tokenmaxxing was never a thing to begin with. Just because a few companies did it doesn't mean it was a widespread phenomenon.
The issue is the companies doing it could spend billions on tokens and they have. I for one know that there are multiple Big Tech Fortune 500 companies that have burnt over 1B in tokens in a single quarter.
This is purely for coding and analogues.
Agreed. There is way too much noise made out of this from a handful of companies.
>I’ve basically never heard a business leader say that they were going to set a bunch of money on fire because it made them feel good.
Really? ~4 years ago our CEO hired a consultant to fly out several times to do team building exercises. We can't afford to do our 3-year server refresh cycle, but the consultant was no problem to pay.
We just recently had branding consultants come in and also spent thousands of dollars (AWS charges) on rebranding all our photos. We operate in a captive market, if you want to operate in our market you are required to subscribe to our service, and if you aren't in our market you can't subscribe. Branding at the end of the day drives 0 sales.
Heck, reminds me of the time a company I was working with hired a new CTO and one of the first things he did was as "server renaming scheme" using obscure (to the US-centric staff) city names from around the world (database servers are Swiss city names, web servers are Denmark, storage is Finland). We went from cattle naming to pet naming, for a CTO that lasted ~6 months.
In my experience company leadership is not quite as thrifty as this article likes to think they are.
> database servers are Swiss city names, web servers are Denmark, storage is Finland
consider me officially triggered
To be fair leaders usually don't say that, they say a whole lot of nothing that means "We're gonna set money on fire because it makes me feel good."
Or more accurately, "Because this is good for my career."
It's AI usage mandates now, but rather than focusing on how the current hot topic has ripped through the business world, often without benefit nor repercussions at leadership, I'd prefer to analyze the higher pattern. We've recently experienced such ripples as the metaverse, blockchain/nft/web3, 'the cloud' (and a minor wave of cloud gaming). There was even a teacup buzz of 'apis', oddly disconnected from the semantic web.
Why do such fever dreams occur at all? Are they getting more prevalent? More damaging? Do they jepaordize the global economy? Should they be regulated in some fashion?
I can't prove my case, but I think it's a symptom of media manipulation/consolidation, the 'fiduciary duty' delusion, and that shareholders can hold the puppet strings tighter than they used to. More and more, they place their sillytown bets and expect the plebs to dance to them.
“Thing is dead, long live thing” is dead, long live “thing is dead, long live thing.”
I do abuse this title format, guilty as charged
Beyond getting momentum going for a cmpany, Tokenmaxxing is lighting money on fire.
The idea of tokenmaxxing reaches different companies in different waves, so it will be discovered in waves and outgrown in waves in companies and industries in their own cycle.
In the long run, tokenmaxxing is like drunken sailor spending. Scaling is almost always about a large component of efficiency, and lighting money on fire in the street can only last so long.