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?
I run a small business with two employees.
N=2 here, of course, but one of them will experiment with any new process you introduce (as well as plenty more that you don't!)
The other will keep doing what he's always been doing, even if it's frustrating and inefficient, unless you monitor him and force him to use the new process.
I could imagine most "normal employers" would understand that both type of person exists and, assuming you're getting good first impressions from group A, it's usually better off in the long run to shove the new process down group B's throat.
(This isn't to say that the "Group B" employee is less valuable or anything - he is more conscientious and reliable than anyone else we've ever hired - but just that different people need different management styles)
> 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.
And here we are. AI use mandates are a humiliation ritual, at least how I've seen them. Because it's not just a matter of making the employees use AI; public criticism or speaking about the drawbacks are also punished. It's get totally on board or get out; if you're not completely gung ho, despite the testimony of your lying eyes, maybe you don't have what it takes to work here, son. It's something they use as a shit test, just like the North Korean dogma that Kim Jong-il scored a perfect 18 holes-in-one every time he stepped on the course: are you willing to compromise your values, to the point of mouthing naked untruths, in total submission to the company's leadership?
Do you actually have a job? Do you talk to your coworkers?
This is an insane take. Plenty of people are critical of AI at my job despite a big push to use it. I find the comparison to NK distasteful, coming from someone who presumably is pretty well paid and can quit their job whenever they want.
If you're feeling humiliated... well, I don't think it's because your boss wants you to try AI.
>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? T
What happens if employees say no power tools are needed and after a few months a competition shows up with power tools and hires a bunch of noobs and beating your production numbers and sales?
Your employees simply may leave the company and work for them and learn the new culture at this new competitor.
Is there any law which prevents people from moving between companies? No? Then the promoters of that company are going to do what they think is fit to keep them in business and stay competitive. Many times they'll be wrong, sometimes they'll be right.
> The logic of buying the tools then forcing the employees to use them "or else" is completely backwards in any sane world
People are stubborn. A lot of productivity improvements had to be almost forced upon farmers, for example. Even when early adopters demonstrated the benefits, a decent fraction of them just didn’t want to change.
> 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?
Are you suggesting that changes to new production technologies are always driven bottom up by line workers? I'm guessing that historically that's rare.
Because people don't know what they want until they have and use it. Faster horses, etc. One can only really implement systemic change from the top down, as Moloch indicates.
> 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.
For one, software tools are cheap, especially with OSS in the mix. You're buying one "tool" and paying for operational expenses that scale with total usage across all company.
But secondly, and more importantly, the "consulting" and discussing was done over the period of last 3 years, by ~1 year ago the high-level conclusions were pretty much locked in, the worthiness of the adoption was blindingly obvious at that point, so I can see why tokenmaxxing would be where this ended up, even though (here I disagree with the article a bit) the tools aren't at the "compounding correctness" stage just yet. It's really quite simple: the stick didn't work (telling people in increasingly direct ways to try using AI for stuff), so they tried the carrot.
$deity knows a good chunk of engineers will inadvertently fall for any trick that involves a scoreboard. That holds even when they're perfectly aware they're being tricked.
> If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
Again, they did that, they've been doing it continuously over past 3 years. Some people are excited, some people don't care, but some - a population that's definitely overrepresented in HN comments - just stubbornly refuse to try. Now that the answers are in, and they speak in favor of AI, the companies are doing what "any normal employer would": trying to get the stubborn employers to do their job they way their bosses want them to.
(In fact, normal employers would be more eager to fire people who keep refusing top-down instructions - but it's also obvious this technology is experimental; the models and harnesses get more powerful faster than people can learn to use them - so carrots make more sense than sticks in this transition period. Stubborn people begrudgingly using those tools offer an entirely unique perspective and explore use cases and approaches that you won't get from excited adopters.)
> 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?
I mean, the difference in the metaphor is that we have pretty fully understood carpentry for many hundreds of years. We still find it difficult to write even simple software to address all our needs, as is evidenced by the insane pay in our industry. Carpenters can suggest tools because they know what's out there. The same was not true about LLMs a year ago.
> That is way too charitable, people were being fired based on these metrics
People get fired for all kinds of reasons including no reason at all. Oftentimes leadership even lies about the real reasons for firing people because they don't sound good!
I'm gonna be blunt: if you're in software and you refuse to use AI for moral reasons, I think you should be fired. There's being principled and there's being obstinate and the difference between the two is how well you can convince people that you _have_ principles. Most LLM-hating people fall short on this point, because
> do I really need to link the Jensen Huang quote?
Sure! Link it again, we all know it's highly immoral when shovel salesmen try to make you want shovels.
> If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
I do not like this HN take of "let's do this thing that works great in small companies and then just blindly pretend that it'll also work at the largest companies in the world!" No, this doesn't work at "normal companies" because you cannot "just ask" 30k+ employees what they want.
Employees, like EVERYONE ELSE, are resistant to change. If I, as CEO of a company, want to get my company to try Claude I have to measure tokens to see if it's getting used. That's it. There's no wave of delusion here.
Because Japanese hand tools are objectively less efficient than power tools in a carpentry shop. The guys that want to use hand tools can go work in a boutique that charges a premium for that level of craftsmanship. If you told them to use power tools, no amount of utility would convince them to use them, with most of their justification being psychological. Also, "It is difficult to get a man to understand something, when his salary depends on his not understanding it."
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 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.
I don’t know, at my company at least tons of devs were holding out on ai usage until the token maxing stuff really started. It was beyond clear by that point that coding agents were a productivity multiplier.
A lot of people believe that. Not a lot of evidence on the table for it (it’s not agent developers’ fault; empirical studies are expensive and rarely live up to scrutiny). Not sure it’s worth forcing people unless you like malicious compliance.
Well here’s where you can level valid complaints against management I think. “Move fast and break things” doesn’t line up super well with “wait for empirical studies to back up your suspicions”
For sure. Just because the studies are incomplete or difficult doesn’t mean they’re useless. We still do unit testing and type systems continue to get more sophisticated and spread further because we believe they have an effect on quality and productivity regardless of the lack of evidence.
However it takes some taste in engineering and perhaps some mathematical sophistication to figure these things out. “Just use AI,” is not a very convincing argument either.
Yeah but if you can't attack the workers and make them hate their lives, are you even a good capitalist? Didn't Milton Friedman die for our bosses right to stomp on our faces in the pursuit of profit?
> who are worried that power tools will replace them
maybe, just maybe, it would have been a better idea to engage with employees first rather than posting on linkedin about how everyone is going to lose their jobs.
cos it's the kinds of people trying to force this stuff on employees that are the ones who have been shouting about that from the rooftops.
If you take LinkedIn at face value everyone who uses the Internet is a sociopath who lives for no purpose beyond maximizing shareholder value.
Seriously, some of the most deranged things I've ever read were by relatively normal people trying to promote themselves on LinkedIn.
What people SAY does not matter nearly as much as what everyone KNOWS and it's pretty damn clear that AI is never going to be able to replace humans in complex domains. Every time a frontier lab announces a breakthrough it's pretty obvious that the setup was more complicated than "hey chat prove the Riemann hypothesis."
The world is gonna need skilled human beings to drive LLMs, no matter how desperately some people like to pretend otherwise.
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.
> 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.
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.
> 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".
The switch away from hand to power tools was a while ago but not, like, ancient history. In the era with fairly widespread literacy and records. Did this sort of check for sawdust thing actually happen?
> 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.
Enterprise plans weren't usage-based until recently. Lots of enterprises were bait-and-switched by AI companies from flat per-seat fees, and now have to go on a token diet to rein-in budgets - which is the blog post's premise about tokenmaxxing being dead.
The retconning is absurd. Companies CxOs's exhibit herd-line behaviors all the time: hiring scrum masters, mandatory return to office, and now tokenmaxxing. FOMO is a sufficient explanation of the behavior, any trend gaining momentum that they fear will give their competition an edge, they will reflexively force adoption with no further reasoning needed. There is no cost to boarding hype trains that go nowhere.
Eh, it’s less hysterical than the ever-pervasive belief among junior devs that they are the smartest people in the room and that all managers everywhere are dumb.
Though I understand that gets social validation from other people with no actual experience.
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".
> Most companies focused entirely on doing "what everyone else is doing"
This is true of my current overlords. It slipped recently that the reason they went AI-nuts was that a competitor had announced going “AI first” and the market responded excitedly. Not because they thought it was a good idea: because the market got excited and they didn't want to get left behind.
This is quite a change as our market is financial services and I remember a time when we had to support decades old browsers (one large UK bank who I won't name here had IE6, and only IE6, on many of its user's machines until ~2017) and web servers because they refused to upgrade anything.
> "to see if Programmer Joe can be as productive as the entire team so we can fire the rest"
I'm not sure who Joe is in our outfit, but I'm certainly in the “the rest who are to be fired” set. I've been unhappy in dev & related for years so the AI revolution which I don't care for is where I'm consciously letting myself get left behind to find something else to do with my life. Haven't touched it. Was too late to claim one of the first tranche of Claude licences. And the second. Oops. Maybe I'll use AI in my next big adventure, or maybe my distaste for it all means I have a grand future waiting for me in the hospitality industry!
At my company, this was the explicitly stated and shared goal from management.
"We can't know all the parts of our business that AI can do a good job automating [because it's so new] but we also don't want to be the last to know and outcompeted along the way. Please throw AI at random parts of your job [and we're tracking this] so we can generate feedback from employees on where to invest in additional automation"
My company has since provided a ton of high-value little AI workflows, alongside a handful that didn't pan out. AI-assisted software development is a major change overall, but the general business-process updates from AI are a net-positive to me.
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.
> Management felt like employees weren't leveraging AI fast enough.
If my productivity is in line with their expectations, I don’t understand why management cares what tools I’m using to do it. No employer ever told me to use emacs instead of vi, even though I’m 10x more productive in one vs the other. So why all of a sudden does management need to micromanage my tools?
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 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.
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.
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.
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.
How many “average C-levels” have you talked to? What, specifically, do you think that actually means? Do you think the average CMO and CTO are identical, and have identical profiles in this case?
Or are you just blathering about things you’ve never experienced because you met the “CEO” of a five person company once? I find grand proclamations by people who speak in TikTok absolutely laughable memeing.
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.
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.
Did they see productivity gains that they're now calibrating for? Why have these productivity gains not been reflected externally in any measurable way?
I'm a +26 on my post so far so it seems like there are a lot of people who agree with me but most replies disagree with me. I suppose this is the nature of online forums - that those who disagree will take the time to reply but those who agree rarely do.
FWIW I agree with you, but it doesn't add much to the conversation to leave a comment saying so.
I also agree with the comment you're replying to as well - the vitriol and anger, along with the "this is just another blockchain bubble" type relies is really interesting. It's so surprising to see the variety of (negative) replies and beliefs people have, along with the general distaste/distrust for management. I guess it's also largely a sign of the times since a lot of ICs probably have a ton of anxiety about their career.
It’s about power and leverage. Software engineers were seen as “gods” in a tech company. Even the crappy ones. Over the last year, really 6 months, they lost great deal of that. Now they’re seen as costs, rather than assets.
This is especially true for the devs who take the code more seriously than the business that employs them. The technical PM who knows a bit of design are suddenly the kings of the company.
> 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
Let us also not think that management is any smarter than any of us and is playing 5D chess games we couldn't comprehend. Notably, games that they also could not articulate when they were making these decisions.
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.
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.
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.
Even modern frontier models benefit so hugely from careful context pruning, maintenance, and rewriting to erase mistakes that it's astonishing to me that there are no tools centered around it. The one tool that used to have such a feature, Zed and its retroactively-named Text Threads, has now stripped itself of it.
> That’s no longer true. We’ve entered a different regime, where spending more tokens generally results in better results. We call this “compounding correctness” — the more tokens you spend on getting a task correct, the more likely you’ll get a good outcome. We talked about this a bit at the last in person Agentics meetup:
Have we? Is it generally the case that the more tokens you spend, you better results you get? This take is so weird I suspect author somehow financially benefits from tokenmaxxing.
> 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.
What I have been doing seems a bit different to what's described, but I always make sure to define how to know the task is done so the agent doesn't quit early. Usually this means telling it to to run the tests and type checks to ensure it runs without errors.
Otherwise they often do a first pass looks good enough but it doesn't actually work.
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.
>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.
The precondition for that is competition. If some company has idiot managers that waste resources on idiotic things, they're supposed to be wiped out by the companies that are actually smart.
Capitalism requires constant evolutionary pressure and a sort of government directed corporation level eugenics program to constantly apply that pressure in order to function properly. Without that, it's just distributed fascism.
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?
You're right, but you'd be lucky if a real human actually reviews any code. At my company, merging a PR still requires 2 humans to press "Approve" but I've been instructed that I don't need to read the PR, I only need to click "Approve". This is what 30 years of SWE experience is being used for now.
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 more likely the junior camper version of "not everything that counts can be counted, and not everything that can be counted counts."
In the early days of LLMs, we saw the classic hype-driven bi-modality of opinions. Folks were in the "fake news, fad" camp, or they were in the "omg, take over the world" camp.
Those of us closer to the space, with the awareness to know that there was some truth (and a lot of misjudgment) to go around, were in the middle of nowhere. When I co-wrote some driver code with Chat GPT, other engineers (and even one of our directors) told me to keep it quiet. At the same time I had directors and VPs asking me how we could accelerate adoption. For a while, I had access to a cheat code just because I had the audacity to not ask for permission. Folks were sure I would get in trouble for spending thousands per month in LLM operation, but a handful came along for the ride, burning tokens like firewood and learning along the way.
Tokenmaxxing is probably coming from at least a few things:
1. A course-correction for the practiced frugality that kept folks from jumping in and just learning at the ragged edge.
2. A willful and deliberate recognition that the best innovations in the later phases of a disruptive introduction often come from sparks of ideation in concentrations of activity. In other words, we don't know where good is, and we need to find it. (Charitable interpretation from the article)
3. Recognition that, even if they don't know why, leaders and product owners will get punished for not jumping in and, because of bullets 1 and 2, won't get punished for trying and missing. Even if they have no idea what they're doing, they're going to fake it until they make it (or slide into another job).
This last set is where the pain lives. An organization with healthy and increasing AI tool
usage will see elevated token counts, but so too will one using LLMs to rewrite wikipedia articles without the letter "m" to keep token counts high. These are pathological behaviors brought on by conflated metrics.
We had discussions about this in the early LLM days, where my old team was looking to ship new capabilities for older products. There was a lengthy VP-level discussion about getting to "80% usage" of the new system vs the old. Because the new system was a superset of the old, I eventually said "we can do that immediately, but it's a cost goal, where we're just aiming to make our business more expensive to operate, rather than a value goal for our users". We didn't adopt the target, but folks were understandably frustrated that they didn't have a straightforward way to measure and report progress.
Tokenmaxxing is, inevitably, a conflated goal, but it's what we have right now. Take advantage of the moment, learn, build, and keep an eye on levers for efficiency.
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.
Your comment implies no ROI on spent tokens. I get a lot more work done tokenmaxxing so the cost is negligible to me 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.
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?
I run a small business with two employees.
N=2 here, of course, but one of them will experiment with any new process you introduce (as well as plenty more that you don't!)
The other will keep doing what he's always been doing, even if it's frustrating and inefficient, unless you monitor him and force him to use the new process.
I could imagine most "normal employers" would understand that both type of person exists and, assuming you're getting good first impressions from group A, it's usually better off in the long run to shove the new process down group B's throat.
(This isn't to say that the "Group B" employee is less valuable or anything - he is more conscientious and reliable than anyone else we've ever hired - but just that different people need different management styles)
> 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.
And here we are. AI use mandates are a humiliation ritual, at least how I've seen them. Because it's not just a matter of making the employees use AI; public criticism or speaking about the drawbacks are also punished. It's get totally on board or get out; if you're not completely gung ho, despite the testimony of your lying eyes, maybe you don't have what it takes to work here, son. It's something they use as a shit test, just like the North Korean dogma that Kim Jong-il scored a perfect 18 holes-in-one every time he stepped on the course: are you willing to compromise your values, to the point of mouthing naked untruths, in total submission to the company's leadership?
Do you actually have a job? Do you talk to your coworkers?
This is an insane take. Plenty of people are critical of AI at my job despite a big push to use it. I find the comparison to NK distasteful, coming from someone who presumably is pretty well paid and can quit their job whenever they want.
If you're feeling humiliated... well, I don't think it's because your boss wants you to try AI.
>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? T
What happens if employees say no power tools are needed and after a few months a competition shows up with power tools and hires a bunch of noobs and beating your production numbers and sales?
Your employees simply may leave the company and work for them and learn the new culture at this new competitor.
Is there any law which prevents people from moving between companies? No? Then the promoters of that company are going to do what they think is fit to keep them in business and stay competitive. Many times they'll be wrong, sometimes they'll be right.
> The logic of buying the tools then forcing the employees to use them "or else" is completely backwards in any sane world
People are stubborn. A lot of productivity improvements had to be almost forced upon farmers, for example. Even when early adopters demonstrated the benefits, a decent fraction of them just didn’t want to change.
> 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?
Are you suggesting that changes to new production technologies are always driven bottom up by line workers? I'm guessing that historically that's rare.
Because people don't know what they want until they have and use it. Faster horses, etc. One can only really implement systemic change from the top down, as Moloch indicates.
> 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.
For one, software tools are cheap, especially with OSS in the mix. You're buying one "tool" and paying for operational expenses that scale with total usage across all company.
But secondly, and more importantly, the "consulting" and discussing was done over the period of last 3 years, by ~1 year ago the high-level conclusions were pretty much locked in, the worthiness of the adoption was blindingly obvious at that point, so I can see why tokenmaxxing would be where this ended up, even though (here I disagree with the article a bit) the tools aren't at the "compounding correctness" stage just yet. It's really quite simple: the stick didn't work (telling people in increasingly direct ways to try using AI for stuff), so they tried the carrot.
$deity knows a good chunk of engineers will inadvertently fall for any trick that involves a scoreboard. That holds even when they're perfectly aware they're being tricked.
> If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
Again, they did that, they've been doing it continuously over past 3 years. Some people are excited, some people don't care, but some - a population that's definitely overrepresented in HN comments - just stubbornly refuse to try. Now that the answers are in, and they speak in favor of AI, the companies are doing what "any normal employer would": trying to get the stubborn employers to do their job they way their bosses want them to.
(In fact, normal employers would be more eager to fire people who keep refusing top-down instructions - but it's also obvious this technology is experimental; the models and harnesses get more powerful faster than people can learn to use them - so carrots make more sense than sticks in this transition period. Stubborn people begrudgingly using those tools offer an entirely unique perspective and explore use cases and approaches that you won't get from excited adopters.)
> 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?
I mean, the difference in the metaphor is that we have pretty fully understood carpentry for many hundreds of years. We still find it difficult to write even simple software to address all our needs, as is evidenced by the insane pay in our industry. Carpenters can suggest tools because they know what's out there. The same was not true about LLMs a year ago.
> That is way too charitable, people were being fired based on these metrics
People get fired for all kinds of reasons including no reason at all. Oftentimes leadership even lies about the real reasons for firing people because they don't sound good!
I'm gonna be blunt: if you're in software and you refuse to use AI for moral reasons, I think you should be fired. There's being principled and there's being obstinate and the difference between the two is how well you can convince people that you _have_ principles. Most LLM-hating people fall short on this point, because
> do I really need to link the Jensen Huang quote?
Sure! Link it again, we all know it's highly immoral when shovel salesmen try to make you want shovels.
> If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
I do not like this HN take of "let's do this thing that works great in small companies and then just blindly pretend that it'll also work at the largest companies in the world!" No, this doesn't work at "normal companies" because you cannot "just ask" 30k+ employees what they want.
Employees, like EVERYONE ELSE, are resistant to change. If I, as CEO of a company, want to get my company to try Claude I have to measure tokens to see if it's getting used. That's it. There's no wave of delusion here.
Because Japanese hand tools are objectively less efficient than power tools in a carpentry shop. The guys that want to use hand tools can go work in a boutique that charges a premium for that level of craftsmanship. If you told them to use power tools, no amount of utility would convince them to use them, with most of their justification being psychological. Also, "It is difficult to get a man to understand something, when his salary depends on his not understanding it."
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 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.
I don’t know, at my company at least tons of devs were holding out on ai usage until the token maxing stuff really started. It was beyond clear by that point that coding agents were a productivity multiplier.
A lot of people believe that. Not a lot of evidence on the table for it (it’s not agent developers’ fault; empirical studies are expensive and rarely live up to scrutiny). Not sure it’s worth forcing people unless you like malicious compliance.
Well here’s where you can level valid complaints against management I think. “Move fast and break things” doesn’t line up super well with “wait for empirical studies to back up your suspicions”
For sure. Just because the studies are incomplete or difficult doesn’t mean they’re useless. We still do unit testing and type systems continue to get more sophisticated and spread further because we believe they have an effect on quality and productivity regardless of the lack of evidence.
However it takes some taste in engineering and perhaps some mathematical sophistication to figure these things out. “Just use AI,” is not a very convincing argument either.
It’ll take time to sort out, I wager.
“Beyond clear” I wouldn’t say that confidently. Even now I’m not sure I agree with that, especially looking at it long term.
Yeah but if you can't attack the workers and make them hate their lives, are you even a good capitalist? Didn't Milton Friedman die for our bosses right to stomp on our faces in the pursuit of profit?
> who are worried that power tools will replace them
maybe, just maybe, it would have been a better idea to engage with employees first rather than posting on linkedin about how everyone is going to lose their jobs.
cos it's the kinds of people trying to force this stuff on employees that are the ones who have been shouting about that from the rooftops.
If you take LinkedIn at face value everyone who uses the Internet is a sociopath who lives for no purpose beyond maximizing shareholder value.
Seriously, some of the most deranged things I've ever read were by relatively normal people trying to promote themselves on LinkedIn.
What people SAY does not matter nearly as much as what everyone KNOWS and it's pretty damn clear that AI is never going to be able to replace humans in complex domains. Every time a frontier lab announces a breakthrough it's pretty obvious that the setup was more complicated than "hey chat prove the Riemann hypothesis."
The world is gonna need skilled human beings to drive LLMs, no matter how desperately some people like to pretend otherwise.
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.
> 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.
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.
Looking for sawdust is a far cry from having a leaderboard of who turned the most wood and electricity into dumpsters full of sawdust
> 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".
The switch away from hand to power tools was a while ago but not, like, ancient history. In the era with fairly widespread literacy and records. Did this sort of check for sawdust thing actually happen?
> 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.
I worked at FAANG. If anything, people are not nearly skeptical enough about how dumb it is with all this going on.
People are (in this analogy) building sawdust farms there.
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.
Enterprise plans weren't usage-based until recently. Lots of enterprises were bait-and-switched by AI companies from flat per-seat fees, and now have to go on a token diet to rein-in budgets - which is the blog post's premise about tokenmaxxing being dead.
The retconning is absurd. Companies CxOs's exhibit herd-line behaviors all the time: hiring scrum masters, mandatory return to office, and now tokenmaxxing. FOMO is a sufficient explanation of the behavior, any trend gaining momentum that they fear will give their competition an edge, they will reflexively force adoption with no further reasoning needed. There is no cost to boarding hype trains that go nowhere.
> overpaid manager class
Ugh. Tell me you're early in career without telling me. Sophomoric take.
Eh, it’s less hysterical than the ever-pervasive belief among junior devs that they are the smartest people in the room and that all managers everywhere are dumb.
Though I understand that gets social validation from other people with no actual experience.
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".
> Most companies focused entirely on doing "what everyone else is doing"
This is true of my current overlords. It slipped recently that the reason they went AI-nuts was that a competitor had announced going “AI first” and the market responded excitedly. Not because they thought it was a good idea: because the market got excited and they didn't want to get left behind.
This is quite a change as our market is financial services and I remember a time when we had to support decades old browsers (one large UK bank who I won't name here had IE6, and only IE6, on many of its user's machines until ~2017) and web servers because they refused to upgrade anything.
> "to see if Programmer Joe can be as productive as the entire team so we can fire the rest"
I'm not sure who Joe is in our outfit, but I'm certainly in the “the rest who are to be fired” set. I've been unhappy in dev & related for years so the AI revolution which I don't care for is where I'm consciously letting myself get left behind to find something else to do with my life. Haven't touched it. Was too late to claim one of the first tranche of Claude licences. And the second. Oops. Maybe I'll use AI in my next big adventure, or maybe my distaste for it all means I have a grand future waiting for me in the hospitality industry!
This is probably the most charitable explanation humanly possible.
Surely for this specific example of managerial stupidity it just is, but I mean more generally, it's a beautiful posting.
I aspire to have this much misplaced belief in any humans at all, let alone CEOs.
At my company, this was the explicitly stated and shared goal from management.
"We can't know all the parts of our business that AI can do a good job automating [because it's so new] but we also don't want to be the last to know and outcompeted along the way. Please throw AI at random parts of your job [and we're tracking this] so we can generate feedback from employees on where to invest in additional automation"
My company has since provided a ton of high-value little AI workflows, alongside a handful that didn't pan out. AI-assisted software development is a major change overall, but the general business-process updates from AI are a net-positive to me.
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.
> Management felt like employees weren't leveraging AI fast enough.
If my productivity is in line with their expectations, I don’t understand why management cares what tools I’m using to do it. No employer ever told me to use emacs instead of vi, even though I’m 10x more productive in one vs the other. So why all of a sudden does management need to micromanage my tools?
Because they're reading blog posts and listening to podcasts that increase their expectations of what your output should be.
Your productivity isn’t in line with their expectations. Maybe your immediate manager but not the executives. That’s why they are doing it.
Their expectations aren't based in reality so I'm not sure why anyone should care
Edit: I mean besides the obvious of "because they will fire you if you don't care"
But idk. They're aiming to fire me eventually and have AI do 100% of my job so meh. Fire me now instead of later.
It's FOMO all the way down.
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.
> 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.
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.
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.
It seems really absurd that anyone would encourage or even force employees to burn more money to see if maybe something works.
You’re post rationalizating
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.
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.
How many “average C-levels” have you talked to? What, specifically, do you think that actually means? Do you think the average CMO and CTO are identical, and have identical profiles in this case?
Or are you just blathering about things you’ve never experienced because you met the “CEO” of a five person company once? I find grand proclamations by people who speak in TikTok absolutely laughable memeing.
The problem is that managers have no idea how this is supposed to help either, and just get told from above to use AI.
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.
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.
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.
It does not seem obviously correct to me.
Did they see productivity gains that they're now calibrating for? Why have these productivity gains not been reflected externally in any measurable way?
Independent of everything else, very interesting to see how polarized the comments are here
I'm a +26 on my post so far so it seems like there are a lot of people who agree with me but most replies disagree with me. I suppose this is the nature of online forums - that those who disagree will take the time to reply but those who agree rarely do.
FWIW I agree with you, but it doesn't add much to the conversation to leave a comment saying so.
I also agree with the comment you're replying to as well - the vitriol and anger, along with the "this is just another blockchain bubble" type relies is really interesting. It's so surprising to see the variety of (negative) replies and beliefs people have, along with the general distaste/distrust for management. I guess it's also largely a sign of the times since a lot of ICs probably have a ton of anxiety about their career.
It’s about power and leverage. Software engineers were seen as “gods” in a tech company. Even the crappy ones. Over the last year, really 6 months, they lost great deal of that. Now they’re seen as costs, rather than assets.
This is especially true for the devs who take the code more seriously than the business that employs them. The technical PM who knows a bit of design are suddenly the kings of the company.
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.
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
lines of code produced. similar dumb metric.
An insane re-writing of the last year of bullshit insanity. Good one.
So this is the narrative now? Come on.
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!
> 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.
Let us also not think that management is any smarter than any of us and is playing 5D chess games we couldn't comprehend. Notably, games that they also could not articulate when they were making these decisions.
> 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.
No one is stupid enough to always measure performance based on token spend and have unlimited budget.
Accenture was.
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.
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.
Even modern frontier models benefit so hugely from careful context pruning, maintenance, and rewriting to erase mistakes that it's astonishing to me that there are no tools centered around it. The one tool that used to have such a feature, Zed and its retroactively-named Text Threads, has now stripped itself of it.
> I was lucky enough to receive a weeklong $50k per head AI training
wow! That sounds like an unbelievable grift. Who were they such that anyone could possibly think that's a worthwhile investment?
> Like, imagine if some serious business leader, like, idk, Mark Zuckerberg, decided to announce that Meta was going to burn money.
Like ... pivoting to the "metaverse" and changing the company name to show he's serious.
> That’s no longer true. We’ve entered a different regime, where spending more tokens generally results in better results. We call this “compounding correctness” — the more tokens you spend on getting a task correct, the more likely you’ll get a good outcome. We talked about this a bit at the last in person Agentics meetup:
Have we? Is it generally the case that the more tokens you spend, you better results you get? This take is so weird I suspect author somehow financially benefits from tokenmaxxing.
> This take is so weird I suspect author somehow financially benefits from tokenmaxxing.
They might own a chunk of NVDA.
it's a huge oversimplification imo. it reminds me of someone worshipping LOC: more = better
This is like hell, if hell was being stuck on a really poorly-maintained uncomfortable rollercoaster forever.
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.
The long live x is a lazy meme that draws attention that posters can use to skip thinking of an actual appropriate title.
that is a better title! Added it as a subheader
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
What I have been doing seems a bit different to what's described, but I always make sure to define how to know the task is done so the agent doesn't quit early. Usually this means telling it to to run the tests and type checks to ensure it runs without errors.
Otherwise they often do a first pass looks good enough but it doesn't actually work.
If you are really engineering, you would really be tokenoptimizing for most quality per token.
Studies have proved that you'd have been better off with fartmaxxing.
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.
>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.
Narratives are the most ungodly effective thing known to mankind, is the issue.
> "capitalism is efficient"
The precondition for that is competition. If some company has idiot managers that waste resources on idiotic things, they're supposed to be wiped out by the companies that are actually smart.
Capitalism requires constant evolutionary pressure and a sort of government directed corporation level eugenics program to constantly apply that pressure in order to function properly. Without that, it's just distributed fascism.
> database servers are Swiss city names, web servers are Denmark, storage is Finland
consider me officially triggered
why name your servers db-us-east-2 and web-de-stuttgart-3 when they could be called grindelwald and silkeborg?
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."
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?
You're right, but you'd be lucky if a real human actually reviews any code. At my company, merging a PR still requires 2 humans to press "Approve" but I've been instructed that I don't need to read the PR, I only need to click "Approve". This is what 30 years of SWE experience is being used for now.
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.
Or like Meta spending $90 billion on "the metaverse" only to see 300,000 users at its peak.
That comes out to spending $300,000 per user.
Funny, now it's the management saying "Go be a bohemian, experiment, spend freely." and the employee saying, "Hold on, where's my ROI?"
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.
This is more likely the junior camper version of "not everything that counts can be counted, and not everything that can be counted counts."
In the early days of LLMs, we saw the classic hype-driven bi-modality of opinions. Folks were in the "fake news, fad" camp, or they were in the "omg, take over the world" camp.
Those of us closer to the space, with the awareness to know that there was some truth (and a lot of misjudgment) to go around, were in the middle of nowhere. When I co-wrote some driver code with Chat GPT, other engineers (and even one of our directors) told me to keep it quiet. At the same time I had directors and VPs asking me how we could accelerate adoption. For a while, I had access to a cheat code just because I had the audacity to not ask for permission. Folks were sure I would get in trouble for spending thousands per month in LLM operation, but a handful came along for the ride, burning tokens like firewood and learning along the way.
Tokenmaxxing is probably coming from at least a few things:
1. A course-correction for the practiced frugality that kept folks from jumping in and just learning at the ragged edge.
2. A willful and deliberate recognition that the best innovations in the later phases of a disruptive introduction often come from sparks of ideation in concentrations of activity. In other words, we don't know where good is, and we need to find it. (Charitable interpretation from the article)
3. Recognition that, even if they don't know why, leaders and product owners will get punished for not jumping in and, because of bullets 1 and 2, won't get punished for trying and missing. Even if they have no idea what they're doing, they're going to fake it until they make it (or slide into another job).
This last set is where the pain lives. An organization with healthy and increasing AI tool usage will see elevated token counts, but so too will one using LLMs to rewrite wikipedia articles without the letter "m" to keep token counts high. These are pathological behaviors brought on by conflated metrics.
We had discussions about this in the early LLM days, where my old team was looking to ship new capabilities for older products. There was a lengthy VP-level discussion about getting to "80% usage" of the new system vs the old. Because the new system was a superset of the old, I eventually said "we can do that immediately, but it's a cost goal, where we're just aiming to make our business more expensive to operate, rather than a value goal for our users". We didn't adopt the target, but folks were understandably frustrated that they didn't have a straightforward way to measure and report progress.
Tokenmaxxing is, inevitably, a conflated goal, but it's what we have right now. Take advantage of the moment, learn, build, and keep an eye on levers for efficiency.
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.
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)
It's actually used properly here.
“Thing is dead, long live thing” is dead, long live “thing is dead, long live thing.”
‘“Thing is dead, long live thing” is all you need’ considered harmful
I do abuse this title format, guilty as charged
Phoenixing considered harmful
Would that be pheonixmaxxing or pheonixxing these days?
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 so the cost is negligible to me 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.