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.
Why would a carpentry shop buy hundreds of thousands of dollars of power tools without consulting with their employees to see what they actually need to get their job done more effectively? The logic of buying the tools then forcing the employees to use them "or else" is completely backwards in any sane world.
(Of course, we've all had bosses that went to some marketing seminar and come back having been tricked^Wsold into buying some wizz-bang widget that we need to now integrate because of a sunk-cost fallacy, but I thought everyone was on the same page that this is not how normal procurement was supposed to work.)
> the point is that if you wanna see if the tools are working you wanna see proof they're actually being used.
That is way too charitable, people were being fired based on these metrics and people were absolutely talking about token burn as being a metric for productivity (do I really need to link the Jensen Huang quote?). That isn't an indication of this hysteria being based on "just trying to see if the tools work".
If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
> If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
because that would require actually admitting that employees are the people in an organisation who are responsible for the success of that organisation, rather than the people higher up the org chart.
The logic of trusting employees who are worried that power tools will replace them to utilize power tools effectively is completely backwards in any sane world. People don’t like change, sometimes it needs to be forced on them.
Doubt. People brought in all kinds of web applications in the early Web 2.0 era because corporate IT was being too stingy (for a lot of reasons). People will find efficiencies on their job on their own. No need to denigrate them.
So do a workshop on power tools, measure their efficacy and the quality of the result, do some demonstration videos on power tools, get people to compare, seek feedback on their usage. Don't count electricity and sawdust, or you'll find people getting very good at expensively turning blocks of wood into sawdust.
The level of trust in leadership is remarkable. There’s reasonable ways to have people try power tools. Have one team use power tools and another hand tools and see the outcome.
The mandate was literally “the more sawdust you create the more money you’ll make”. Nothing of value is learned by that mandate. Sure it’ll make people use power tools but it won’t cause anyone to learn how to use them to make furniture.
They might understand the danger of bad metric but that doesn’t mean they aren’t victims of them. If there was intentionality here it was lazy as hell at best.
> 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.
Or count the fingers, I guess. It's all fun and games until someone looses AI.
> the people who run FAANG don't understand the dangers of bad metrics is... interesting
They don't. They want some metric to support what they want to do and don't care about good metrics at all.
I've spent the vast majority of my career in FAANGs and it's been the pattern everywhere.
Right now my org has a senior director who is constantly battering managers to tell their reports to fill out the weekly surveys.
Why are the employees not filling out the surveys? Because instead of the old once a year large survey with questions about various levels (including local teams where management cared about the numbers and I could see the actions they took) we now get a survey every week with questions that are meaningless and I have no answer for.
"How does team X deliver on its priorities"?
Team X has O(10K) peoples and a barely countable infinity of projects. Most of which I don't know about and most of which I'm not supposed to know about since things are compartmentalized. So I don't know what team X's priorities are, I don't know how they deliver on them, and I never will know. Asking me and my colleagues is a waste of time and money.
...but none of that matters because the directors want "data" and they want a dashboard showing that we're all giving them "data".
Bad managers, in general, grab a metric and then unthinkingly optimize it. I’ve never worked for FAANG, but I’d be surprised if they didn’t have bad managers too.
> suggesting that the people who run FAANG don't understand the dangers of bad metrics is... interesting.
from my time in FAANG... that seems about correct. Probably the people at the absolute top don't want to just pointlessly burn tokens, but pass that down the chain and eventually the rumor mill turns that into "tokens are an input for your performance review" and people start running Wiggum loops to fix minor typos or linters or something—especially if you do it at a time when every company seems to be doing layoffs.
> but suggesting that the people who run FAANG don't understand the dangers of bad metrics is... interesting
You're far too charitable. Understanding has nothing to do with it. Big companies are too far insulated from bad metrics. Middle managers get away with anything and everything because their decisions are too far removed from reality. And they're nowhere to be seen when the other shoe drops. And they'll just leave to a promotion elsewhere if they stay and results are bad.
Everything is far removed from reality in bigco. So you get a bunch of theater and house-playing with "data-driven" posters up on the wall. It's a 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"
I would wager most if not all of the tokenmaxxing was done on enterprise API priced plans, not subscription plans. You can't actually token"max" if you are limited in the amount of tokens you can use per 5 hours.
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".
An interesting side effect of this spreading across social media is that even companies without token leaderboards were having problems with needless tokenmaxxing.
When everyone was reading about token leaderboards on all of their social media channels (include social news sites like Reddit and Hacker News) it created token anxiety even at companies that didn’t want a leaderboard. Programmers were afraid that their managers would be secretly ranking them based on token usage and they needed to pump up those numbers to avoid layoffs.
Once teams implemented token budgets in response it creates an ugly situation where a few people feel the need to use as many tokens as they can at the beginning of the budget window to stay ahead.
It’s really frustrating to have this phenomenon leak into a company that was never encouraging or looking for high token use.
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.
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.
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.
This reminds me of the popular opinion on HN for return to office mandates as executives wanting to recover their real estate investments.
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.
The smart move would have been to get lower level managers to assign specific employees to experiment with applying LLMs to their processes and report back. Then incorpoate the findings into their processes.
Instead there was FOMO mass hysteria. Now there is a backlash. And a lot of time and money wasted.
Its not _just_ that. Orgs aren't remotely sensible at measuring anything that isn't counted in dollars.
employees who are on the ai bandwagon are there for the free management attention.
Management is cooked because the damn market is hard, money is tight and they can't afford to fight the top down love and $$$ thrown at AI.
If you zoom out, all the real money spent on energy to keep AI alive isn't going to be held in nvidia stock for too long. it will burst, but its stupid to time it.
> Orgs aren't remotely sensible at measuring anything that isn't counted in dollars.
A sensible organization machinery will move to optimize the metrics that make money. Often times figuring out said machinery takes iterations. Some of them are idiotic (ref: tokenmaxxing) but they are generally directionally correct.
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.
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.
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
HN opinions are usually divided into individual contributor vs management battles. Usually the IC opinion is majority because most people here are likely ICs.
At the IC level, people don't sense the impending urgency for the overall business. They usually sense the urgency for themselves first. AI has completely changed the software industry in 6 months. We went from having AI write some code and copy/pasting to having AI write 99% of the code in 6 months. SaaS went from nice UX and CRUD code logic being a moat to these being nearly free.
Big software companies have to adapt to this new world or they will be outcompeted by smaller, newer, nimbler companies. That's what management is thinking. For ICs, they're usually thinking about their own jobs first.
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.
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.
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.
Folks have been saying “things are different now, the agents are now compounding success instead of error” for at least a year now, but I just don’t see it. I was lucky enough to receive a weeklong $50k per head AI training from the people saying these things, and one of their few helpful concrete recommendations was to constantly clear context all the time, to avoid things going off the rails.
However, I think finding security vulnerabilities is one use case where it doesn’t matter. Tokenmaxxing is absolutely effective for that. We as an industry are in the middle of adopting very expensive, complex continuous fuzzers.
This seems to happen with most big tech adoption in the first few years. The big data boom in the early 2010's had execs just buying up spark clusters and data lakes before they even had a clear analytical use case or governance.
> 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.
>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.
I'm also taken aback with how naive folks are about companies, they really seem to have bought the whole "capitalism is efficient" maxim hook, line, and sinker.
I really struggle to imagine how anyone in a corporate environment has managed to never run into obvious examples of waste like you describe (overpaid consultants and mandatory budgets are classic examples). Office Space came out 27 years ago and has a plotline making fun of overpaid "efficiency consultants" whose only job is to tell management to fire people.
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.
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.
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.
Your comment implies no ROI on spent tokens. I get a lot more work done tokenmaxxing but YMMV. Of course there's no point in tokenmaxxing if you don't have enough work available to scale beyond yourself, or you're unable to use AI to do so.
I predict startups will continue to tokenmaxx while 40,000+ person companies will become a little more conservative.
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 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.
Why would a carpentry shop buy hundreds of thousands of dollars of power tools without consulting with their employees to see what they actually need to get their job done more effectively? The logic of buying the tools then forcing the employees to use them "or else" is completely backwards in any sane world.
(Of course, we've all had bosses that went to some marketing seminar and come back having been tricked^Wsold into buying some wizz-bang widget that we need to now integrate because of a sunk-cost fallacy, but I thought everyone was on the same page that this is not how normal procurement was supposed to work.)
> the point is that if you wanna see if the tools are working you wanna see proof they're actually being used.
That is way too charitable, people were being fired based on these metrics and people were absolutely talking about token burn as being a metric for productivity (do I really need to link the Jensen Huang quote?). That isn't an indication of this hysteria being based on "just trying to see if the tools work".
If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
> If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
because that would require actually admitting that employees are the people in an organisation who are responsible for the success of that organisation, rather than the people higher up the org chart.
The logic of trusting employees who are worried that power tools will replace them to utilize power tools effectively is completely backwards in any sane world. People don’t like change, sometimes it needs to be forced on them.
Doubt. People brought in all kinds of web applications in the early Web 2.0 era because corporate IT was being too stingy (for a lot of reasons). People will find efficiencies on their job on their own. No need to denigrate them.
[delayed]
Because those power tools had just been invented and no one had experience with them.
Though in theory power tools are faster than hand tools.
So do a workshop on power tools, measure their efficacy and the quality of the result, do some demonstration videos on power tools, get people to compare, seek feedback on their usage. Don't count electricity and sawdust, or you'll find people getting very good at expensively turning blocks of wood into sawdust.
The level of trust in leadership is remarkable. There’s reasonable ways to have people try power tools. Have one team use power tools and another hand tools and see the outcome.
The mandate was literally “the more sawdust you create the more money you’ll make”. Nothing of value is learned by that mandate. Sure it’ll make people use power tools but it won’t cause anyone to learn how to use them to make furniture.
They might understand the danger of bad metric but that doesn’t mean they aren’t victims of them. If there was intentionality here it was lazy as hell at best.
> 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.
Or count the fingers, I guess. It's all fun and games until someone looses AI.
> the people who run FAANG don't understand the dangers of bad metrics is... interesting
They don't. They want some metric to support what they want to do and don't care about good metrics at all.
I've spent the vast majority of my career in FAANGs and it's been the pattern everywhere.
Right now my org has a senior director who is constantly battering managers to tell their reports to fill out the weekly surveys.
Why are the employees not filling out the surveys? Because instead of the old once a year large survey with questions about various levels (including local teams where management cared about the numbers and I could see the actions they took) we now get a survey every week with questions that are meaningless and I have no answer for.
"How does team X deliver on its priorities"?
Team X has O(10K) peoples and a barely countable infinity of projects. Most of which I don't know about and most of which I'm not supposed to know about since things are compartmentalized. So I don't know what team X's priorities are, I don't know how they deliver on them, and I never will know. Asking me and my colleagues is a waste of time and money.
...but none of that matters because the directors want "data" and they want a dashboard showing that we're all giving them "data".
Bad managers, in general, grab a metric and then unthinkingly optimize it. I’ve never worked for FAANG, but I’d be surprised if they didn’t have bad managers too.
> suggesting that the people who run FAANG don't understand the dangers of bad metrics is... interesting.
from my time in FAANG... that seems about correct. Probably the people at the absolute top don't want to just pointlessly burn tokens, but pass that down the chain and eventually the rumor mill turns that into "tokens are an input for your performance review" and people start running Wiggum loops to fix minor typos or linters or something—especially if you do it at a time when every company seems to be doing layoffs.
> but suggesting that the people who run FAANG don't understand the dangers of bad metrics is... interesting
You're far too charitable. Understanding has nothing to do with it. Big companies are too far insulated from bad metrics. Middle managers get away with anything and everything because their decisions are too far removed from reality. And they're nowhere to be seen when the other shoe drops. And they'll just leave to a promotion elsewhere if they stay and results are bad.
Everything is far removed from reality in bigco. So you get a bunch of theater and house-playing with "data-driven" posters up on the wall. It's a 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"
I would wager most if not all of the tokenmaxxing was done on enterprise API priced plans, not subscription plans. You can't actually token"max" if you are limited in the amount of tokens you can use per 5 hours.
Did not read the twitter thread but I think it is a mix of some companies with above strategy and most others just cargo culting
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".
It seems really absurd that anyone would encourage or even force employees to burn more money to see if maybe something works.
An interesting side effect of this spreading across social media is that even companies without token leaderboards were having problems with needless tokenmaxxing.
When everyone was reading about token leaderboards on all of their social media channels (include social news sites like Reddit and Hacker News) it created token anxiety even at companies that didn’t want a leaderboard. Programmers were afraid that their managers would be secretly ranking them based on token usage and they needed to pump up those numbers to avoid layoffs.
Once teams implemented token budgets in response it creates an ugly situation where a few people feel the need to use as many tokens as they can at the beginning of the budget window to stay ahead.
It’s really frustrating to have this phenomenon leak into a company that was never encouraging or looking for high token use.
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.
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.
> 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.
This reminds me of the popular opinion on HN for return to office mandates as executives wanting to recover their real estate investments.
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.
The smart move would have been to get lower level managers to assign specific employees to experiment with applying LLMs to their processes and report back. Then incorpoate the findings into their processes.
Instead there was FOMO mass hysteria. Now there is a backlash. And a lot of time and money wasted.
Letting everybody freely experiment for a while is much more effective than appointing somebody to do just that.
Freely experiment sure. But you're not doing an effective experiment if you tell people they'll be graded on how many tokens they use.
Its not _just_ that. Orgs aren't remotely sensible at measuring anything that isn't counted in dollars.
employees who are on the ai bandwagon are there for the free management attention.
Management is cooked because the damn market is hard, money is tight and they can't afford to fight the top down love and $$$ thrown at AI.
If you zoom out, all the real money spent on energy to keep AI alive isn't going to be held in nvidia stock for too long. it will burst, but its stupid to time it.
> Orgs aren't remotely sensible at measuring anything that isn't counted in dollars.
A sensible organization machinery will move to optimize the metrics that make money. Often times figuring out said machinery takes iterations. Some of them are idiotic (ref: tokenmaxxing) but they are generally directionally correct.
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.
You’re post rationalizating
The problem is that managers have no idea how this is supposed to help either, and just get told from above to use AI.
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.
Independent of everything else, very interesting to see how polarized the comments are here
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
HN opinions are usually divided into individual contributor vs management battles. Usually the IC opinion is majority because most people here are likely ICs.
At the IC level, people don't sense the impending urgency for the overall business. They usually sense the urgency for themselves first. AI has completely changed the software industry in 6 months. We went from having AI write some code and copy/pasting to having AI write 99% of the code in 6 months. SaaS went from nice UX and CRUD code logic being a moat to these being nearly free.
Big software companies have to adapt to this new world or they will be outcompeted by smaller, newer, nimbler companies. That's what management is thinking. For ICs, they're usually thinking about their own jobs first.
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 one is stupid enough to always measure performance based on token spend and have unlimited budget.
Accenture was.
Thanks for posting the tweet, it was a very interesting read. A bit amusing knowing what's up with MS and Azure these days, but that's not the point!
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.
An insane re-writing of the last year of bullshit insanity. Good one.
> 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.
> 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.
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.
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.
> 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.
Folks have been saying “things are different now, the agents are now compounding success instead of error” for at least a year now, but I just don’t see it. I was lucky enough to receive a weeklong $50k per head AI training from the people saying these things, and one of their few helpful concrete recommendations was to constantly clear context all the time, to avoid things going off the rails.
However, I think finding security vulnerabilities is one use case where it doesn’t matter. Tokenmaxxing is absolutely effective for that. We as an industry are in the middle of adopting very expensive, complex continuous fuzzers.
This seems to happen with most big tech adoption in the first few years. The big data boom in the early 2010's had execs just buying up spark clusters and data lakes before they even had a clear analytical use case or governance.
Better title more in line with the content of the article would have been: The reports of tokenmaxxing’s death are greatly exaggerated.
Pet peeve of mine is nonsensical usage of the x is dead, long live x.
that is a better title! Added it as a subheader
The long live x is a lazy meme that draws attention that posters can use to skip thinking of an actual appropriate title.
At least it's being used. There are many examples of tech over-adoption, like building out capacity for 1M concurrent users, only to see 50.
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?
Loop "engineering" has now become a thing now apparently (a la prompt "engineering") https://github.com/topics/loop-engineering
> 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
>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
I'm also taken aback with how naive folks are about companies, they really seem to have bought the whole "capitalism is efficient" maxim hook, line, and sinker.
I really struggle to imagine how anyone in a corporate environment has managed to never run into obvious examples of waste like you describe (overpaid consultants and mandatory budgets are classic examples). Office Space came out 27 years ago and has a plotline making fun of overpaid "efficiency consultants" whose only job is to tell management to fire people.
Narratives are the most ungodly effective thing known to mankind, is the issue.
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."
I don’t think people who write these headlines understand that “long live the king” used to refer to the next king. Where is the next tokenmaxxing?
(its in the article, which predicts that there will be another round of tokenmaxxing with different underlying incentives)
Funny, now it's the management saying "Go be a bohemian, experiment, spend freely." and the employee saying, "Hold on, where's my ROI?"
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.
Tokenmaxxing was never a thing to begin with. Just because a few companies did it doesn't mean it was a widespread phenomenon.
> Tokenmaxxing was never a thing to begin with.
Anecdote, I thought so too until the company I work just instated this where you have spend from 35-60K within 6 months. Insanity
Agreed. There is way too much noise made out of this from a handful of companies.
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.
“Thing is dead, long live thing” is dead, long live “thing is dead, long live thing.”
Phoenixing considered harmful
Would that be pheonixmaxxing or pheonixxing these days?
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.
Your comment implies no ROI on spent tokens. I get a lot more work done tokenmaxxing but YMMV. Of course there's no point in tokenmaxxing if you don't have enough work available to scale beyond yourself, or you're unable to use AI to do so.
I predict startups will continue to tokenmaxx while 40,000+ person companies will become a little more conservative.
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?