12 ms·

Tokenmaxxing is dead, long live tokenmaxxing

• Mona1 4mo ago
  [dead]
• aurareturn 4mo ago
  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 https://x.com/danluu/status/1487228574608211969?lang=en
  • Chu4eeno 4mo ago
    The problem is that managers have no idea how this is supposed to help either, and just get told from above to use AI.
  • herval 4mo ago
    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".
    • dspillett 4mo ago
      > 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!
      • robocat 4mo ago
        Isn't it easier to get a job when you already have a job? There's some jobs I'd love to do, but I can't face the bullshit of tertiary education again. Without some sort of ticket, job choices become more limited?
        • dspillett 4mo ago
          > Isn't it easier to get a job when you already have a job? Yes. Or so I'm told, I've not needed to apply for a job for 26 years… I have something possible available, though whether it still will be in five months (the earliest I'm likely to leave because of [reasons] and a two-month notice period) is a bit unknown. That five months might be ten as there are other major changes in the company (we were bought a while ago) from which the dust should have settled by Feb, and it makes sense to try to hold out that long to see if I'm still hating things with the same passion at that point. Without that “something” there are less certain tech based options I could look at, and to be honest I really could do with a proper sabbatical style break. The mortgage is paid, I have savings, and no dependents other than the cats, so I have the luxury of considering that option. And if all else fails I've actually done the arithmetic and I can survive on minimum wage for an extended time if I need to, and hospitality work is something friends can get me into above the many others looking (that bit is less of a joke then people assume: it is seriously part of my plans D & E if I can't stick with A and B & C completely fall through).
  • linsomniac 4mo ago
    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.
    • sevenseacat 4mo ago
      I'm in the boat of wondering how so many people run into session limits so often. I have never hit one, except once when Claude Design came out and I had fun generating a bunch of random things to see what it could do (not with the intent of actually using any of the generated designs/code, because it all sucked).
      • linsomniac 4mo ago
        I'm using the $200/mo Claude, and I'll often hit the 5 hour limit, but last week was the first or second time I've hit the week limit. I run pretty much everything on "/effort max" because I've had good results, and I've had plenty of quota left usually, and I want to worry less about "am I getting the best results". Fable, for the few days I had it, would eat through tokens pretty quickly, largely because it tended to work much more on its own. I could give it a task and after asking a few questions it would go off and work for 4-6 hours and be done. I also run a lot of experiments. I'm trying to be a resource that the rest of my team can learn from as far as what works. For example: when one of the people from our parent company asked about automating payroll entry, I threw their documents and discussion at Claude to see what it'd build. That plus churning on their feedback was ~30 hours of API usage right there. I'm currently experimenting with "loops", and using codex in those loops to provide feedback and review. That gives me fable-like autonamy (that 30 hours of API usage above), maybe even better. But it uses a lot of tokens. Loops is the bulk of why I got to the weekly limit last week. Plus I'm having it build an experiment on what my ideal "agent mux" would look like. Herdr is really close, I found it after I started that experiment. Now I'm just letting it run when I have spare usage to see what it comes up with.
  • arexxbifs 4mo ago
    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.
  • witx 4mo ago
    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
    • aurareturn 4mo ago
      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.
      • therein 4mo ago
        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.
        • aurareturn 4mo ago
          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.
      • SecretDreams 4mo ago
        > 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.
      • jdiff 4mo ago
        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.
  • clickety_clack 4mo ago
    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.
    • tsunamifury 4mo ago
      This exactly. Gartner and McKinsey were paid by openAI and Anthropic to sell executive teams on AI usages 20xing profits while cutting spend 70%. And if they don’t immediately make the front end investment now they would be left behind by their competitors. The presentations were convincing and many bought large upfront wholesale tokens then forced them on their employees. When the savings didn’t materialize and neither did the profits. And the spend was no longer going down but up, many execs rather than admit they were duped began blaming workers at scale for not making up for their stupid decision. This is the “get them addicted” part of the platform play. The problem is unlike any successful drug this was expensive and low payoff.
  • catlifeonmars 4mo ago
    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.
    • aurareturn 4mo ago
      Do you have a source for this? Yes, my own company's decision and logic.
      • nullsanity 4mo ago
        [dead]
  • flunhat 4mo ago
    An insane re-writing of the last year of bullshit insanity. Good one.
  • therein 4mo ago
    > 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.
    • no-name-here 4mo ago
      > to cause cognitive atrophy in your employees so that you lose your ability to independently operate your business The argument is tokenmaxxing was put in place by companies, with the goal of causing their employees to lose knowledge?
    • IanCal 4mo ago
      This feels like it’s on the level of claiming conspiracy theories are invented by tin foil companies to sell more hats.
  • danny_codes 4mo ago
    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.
    • aurareturn 4mo ago
      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.
      • socialcommenter 4mo ago
        Out of $13Bln of 2025 revenue, OpenAI received $867 million from one customer (less charitably, one bankroller), SoftBank. And $300 million from Microsoft[0]. That's more than a drop in the bucket, especially given that they're not the only players complicit in being both an investor and a customer. Also are we sure it's all at arm's length? Barring a full audit, it's not possible to guarantee that there's no round-tripping or overstating of revenue. With Microsoft also being a provider for OpenAI, they could be creatively using set-off, or using SG&A, in order to overstate their revenue/gross margin/inference profit margin. I of course have no proof, extraordinary claims etc. etc. It's unlikely but we should at least debate the possibility. They have such a huge collective incentive to do it. [0]: https://www.wheresyoured.at/exclusive-openai-financials/ https://www.wheresyoured.at/exclusive-openai-financials/ (no affiliation with the website owner, who has a unique bias in this)
        • aurareturn 4mo ago
          Are we not all getting timeout issues from Claude Code and Codex frequently due to too much demand?
  • Scene_Cast2 4mo ago
    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.
    • theahura 4mo ago
      Dan Luu at MS: https://x.com/danluu/status/1487228574608211969?lang=en https://x.com/danluu/status/1487228574608211969?lang=en
      • aurareturn 4mo ago
        This is exactly it.
  • throwatdem12311 4mo ago
    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.
    • jmye 4mo ago
      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.
      • otabdeveloper4 4mo ago
        You don't need to meet these C-levels personally. They spread their insane hot AI takes everywhere and go out of their way to market this crap at conferences, etc.
        • TeMPOraL 4mo ago
          Did you read those hot takes personally, or only had them reported on by your favorite YouTube/TikTok pundits? Hint: YouTubers and Tiktokers are in business, and that business is entertainment, and they're about as truthful as a fortune teller. (Difference being, one of these groups is just lying about objective reality that's trivial to independently verify, the other one are just unlicensed therapists with thousand years old rituals).
    • IanCal 4mo ago
      > like having a single engineer spend 250k in tokens or he’d fire him; That’s not quite what was said there, he’s budgeting half a devs salary as token spend in a podcast and that if he had a 500k engineer who spent 5k on it at the end of the year he’d go ape shit. Now you can say that’s wild, and sure, but this is not a standard c suite exec talking it’s the ceo of Nvidia. Even ignoring other hiring costs this is essentially an argument that Nvidia top engineers should get more than a 50% performance improvement with extremely heavy AI usage. To me, that doesn’t seem like such an enormous statement. For the head of a multi trillion dollar company entirely driven by AI sales arguing it gives a useful benefit to engineers isn’t that odd and betting on a 50% improvement within Nvidia seems kinda normal. > Seriously have you ever actually talked to an average C-Level about AI? Yes. Single digit percentage improvements over time would normally excite them, the idea of cappable cost performance improvements that last which your devs actually want to experiment with and a cultural and customer expectation that you’re doing this is pretty enticing. Particularly during a time when tokens were heavily subsidised - isn’t that the perfect time to do it? Now that has ended there’s a huge focus on roi.
  • watwut 4mo ago
    > 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.
  • deleted 4mo ago
    [deleted]
  • theahura 4mo ago
    Independent of everything else, very interesting to see how polarized the comments are here
    • aurareturn 4mo ago
      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.
      • vineyardmike 4mo ago
        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.
        • aurareturn 4mo ago
          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.
      • latexr 4mo ago
        > 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. Why would those who agree “take the time to reply”? To say what? “This”? “Agreed”? “This guy knows it”? Those comments don’t add anything of value. When you agree, it only makes sense to reply if you have something to say which wasn’t covered by the original argument.
  • nitwit005 4mo ago
    > 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.
  • qntmfred 4mo ago
    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
    • aurareturn 4mo ago
      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.
    • Sharlin 4mo ago
      It does not seem obviously correct to me.
  • dgellow 4mo ago
    You’re post rationalizating
    • deleted 4mo ago
      [deleted]
  • SilverElfin 4mo ago
    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.
  • Aurornis 4mo ago
    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.
  • chairmansteve 4mo ago
    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.
    • JV00 4mo ago
      Letting everybody freely experiment for a while is much more effective than appointing somebody to do just that.
      • JoshTriplett 4mo ago
        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.
        • JV00 4mo ago
          I agree with you, but I was answering parent who suggested appointing specific people.
        • deleted 4mo ago
          [deleted]
  • gofreddygo 4mo ago
    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.
    • ngm7 4mo ago
      > 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.
  • gamblor956 4mo ago
    No one is stupid enough to always measure performance based on token spend and have unlimited budget. Accenture was.
  • neonstatic 4mo ago
    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!
  • lezojeda 4mo ago
    [dead]
  • pier25 4mo ago
    It seems really absurd that anyone would encourage or even force employees to burn more money to see if maybe something works.
    • IanCal 4mo ago
      Why? This is literally what experimentation and prototyping is! You spend money for a potential benefit. In this case it’s also a one off cost to find things that can save money over time.
      • pier25 4mo ago
        One thing is to invest R&D money with a strategy and another to force people to burn as much money as possible to see what happens.
  • ab71e5 4mo ago
    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
  • hansmayer 4mo ago
    [dead]
  • ryandrake 4mo ago
    > 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?
    • Andrex 4mo ago
      It's FOMO all the way down.
    • aurareturn 4mo ago
      Your productivity isn’t in line with their expectations. Maybe your immediate manager but not the executives. That’s why they are doing it.
      • bluefirebrand 4mo ago
        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.
    • moduspol 4mo ago
      Because they're reading blog posts and listening to podcasts that increase their expectations of what your output should be.
    • lmm 4mo ago
      > why all of a sudden does management need to micromanage my tools? Because doing so increases the value of their stock options. They might privately think it's as dumb as you do, but apparently the stock market disagrees.
    • IanCal 4mo ago
      Expectations shift, and tools do matter. Imagine you had a direct report. They were doing just fine, slightly better than a typical report. Then you found out they were writing all their code in notepad - no linting, no automated tests or live updates, no refactoring tools, no highlighting or any code search. They didn’t have any cross code searches and didn’t have any documentation. When they hit a problem, they’d churn away at it and never reach for docs, google or so. Still, their performance is in line with what you’d expect from someone in their position. Would getting them to try emacs, vi, linters, etc be micromanaging them? Do you think they’d perform better with them? They are performing in line with expectations for the role, so why bother with something you think would make them more efficient? I’ve made this obviously over the top, and can hear already replies from other bemoaning my comparison while missing the point — tools do matter and if you genuinely believe that a developer could be more efficient working in a different way it makes sense to not only want them to try it but to actively fund that change. Hell, this is literally what we argue for in training! Spend money to make someone better at their job! If you think AI tools make you worse or don’t and can’t help, then that’s one thing. But it makes sense for management if they think it might to spend money on it and to get you to try. Not only this, but wasn’t everyone here shouting about how tokens were subsidised and it couldn’t last? If so, wasn’t the first half of this year a really excellent cheap time to do the maxxing?
  • jdiff 4mo ago
    Did they see productivity gains that they're now calibrating for? Why have these productivity gains not been reflected externally in any measurable way?
  • animuchan 4mo ago
    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.
    • vineyardmike 4mo ago
      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.
    • manicennui 4mo ago
      I doubt the author of the article even believes it. The article is an ad for their services which just happen to be "helping" companies use AI.
  • gsich 4mo ago
    lines of code produced. similar dumb metric.
  • regexorcist 4mo ago
    So this is the narrative now? Come on.
  • CobrastanJorji 4mo ago
    It's simpler. Management felt like employees weren't leveraging AI fast enough. They chose to measure "AI leveraging" in the easiest way they could: how many tokens each employee was using. Goodhart's Law ("When a measure becomes a target, it ceases to be a good measure") immediately triggered.
  • rendaw 4mo ago
    This is obviously wrong. Management has never cared about how engineers do their job. There's never been a push for any other productivity boosting technology: better languages, better editors, automated refactorings, paid code intelligence tools, etc. But suddenly AI comes along and the CEO says "all developers need to write code entirely with LLMs".
    • IanCal 4mo ago
      This is absolute nonsense. Management in many places cares enormously about productivity. What’s been a bit different here is a huge claim of improvement other companies are seeing (so you’re going to be left behind), alongside some developers going off and doing this anyway sending proprietary code hither and thither, alongside some devs railing against the very concept of using it. It’s also a wildly powerful tool and how to use it hasn’t been as clear (where does it provide value, where does it not, what can and can’t it do) so experimentation is really important.
      • rendaw 4mo ago
        I did not say that management doesn't care about productivity. To be clear though, I did mean to say upper management.
  • Forgeties79 4mo ago
    > Now they know what’s possible and what’s not. They really don’t IMO. Hell most of the companies pushing these tools don’t even agree what LLMs are for or are capable of. Too many people are trying to use it to cut too many corners on their work (making more work for everyone else) or are using it to attempt things they don’t know how to do, which means they are incapable of vetting the results, (vibe coding anyone?) which means more instances of the first case or even getting hurt.
  • elvis10ten 4mo ago
    Were there cheaper and humane ways to get more employees to use AI? (yes). Did many people JUST burn tokens (goodbart law)? (Yes). Would people revert back to the mean? (I think yes). Do many professionals hate AI because of this push? (Yes). Was the org net productive? I wish there was an independent body truly assessing the impact of big tech decisions and running counterfactuals. Instead of accepting nice stories like this as a given. Using Claude, I recently tried to do something similar for the Covid hiring spree: https://claude.ai/public/artifacts/21bba86a-ad5d-439c-861d-0e560ebd04c1 https://claude.ai/public/artifacts/21bba86a-ad5d-439c-861d-0...
  • socialcommenter 4mo ago
    Interesting take - upvoted you. I'm not convinced it's been the optimal management strategy, but you're succinctly explaining what they have done, not what they should have done, and in that sense you have a good point. Still leaves huge questions about ROI ($26tln of TAM, anyone???) and doesn't quell the concerns brought forward by AI detractors though.
• linsomniac 4mo ago
  >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.
  • EA-3167 4mo ago
    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."
  • dijksterhuis 4mo ago
    > database servers are Swiss city names, web servers are Denmark, storage is Finland consider me officially triggered
    • hmry 4mo ago
      why name your servers db-us-east-2 and web-de-stuttgart-3 when they could be called grindelwald and silkeborg?
      • deleted 4mo ago
        [deleted]
  • 4mo ago
• baconmania 4mo ago
  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.
  • BobbyJo 4mo ago
    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.
  • tough 4mo ago
    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"
    • Anon1096 4mo ago
      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.
      • overfeed 4mo ago
        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.
  • SR2Z 4mo ago
    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.
• behnamoh 4mo ago
  Tokenmaxxing was never a thing to begin with. Just because a few companies did it doesn't mean it was a widespread phenomenon.
  • aurareturn 4mo ago
    Agreed. There is way too much noise made out of this from a handful of companies.
  • minraws 4mo ago
    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.
  • metaltyphoon 4mo ago
    > 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
  • koiueo 4mo ago
    Maxxing is just a catchy and imprecise name. In my current company nobody forces you to use more tokens, but you're encouraged to write a 300 lines markdown skill.md which takes 8 minutes and costs 5 bucks to execute. That, instead of writing a 200 lines bash script doing all the same thing, but in a deterministic fashion, completing in under 5 seconds and costing 0 if you're not careful with rounding.
• j45 4mo ago
  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.
  • solenoid0937 4mo ago
    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.
• fraywing 4mo ago
  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?
  • leptons 4mo ago
    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.
• gausswho 4mo ago
  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.
  • jackb4040 4mo ago
    The dominance of finance capital over industrial capital reaching its absurd conclusion. NFT mania was only possible because we don't make anything here, no one has a serious plan to reshore and start making things here again, and we can't indefinitely maintain control of production we've exported to the 3rd world indefinitely. So you might as well play these symbolic games and increase your slice of the pie while the music is still playing.
• theanonymousone 4mo ago
  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?
  • jsemrau 4mo ago
    [dead]
  • throwaway89201 4mo ago
    > 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 https://awesomeclaude.ai/ralph-wiggum
    • SchemaLoad 4mo ago
      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.
  • untwerp 4mo ago
    Loop "engineering" has now become a thing now apparently (a la prompt "engineering") https://github.com/topics/loop-engineering https://github.com/topics/loop-engineering
  • panarky 4mo ago
    > Just repeating the same prompt ... If you were tokenmaxxing you would understand.
    • 4mo ago
• impish9208 4mo ago
  “Thing is dead, long live thing” is dead, long live “thing is dead, long live thing.”
  • theahura 4mo ago
    I do abuse this title format, guilty as charged
  • falcor84 4mo ago
    Phoenixing considered harmful
    • cyphar 4mo ago
      Would that be pheonixmaxxing or pheonixxing these days?
  • dofm 4mo ago
    ‘“Thing is dead, long live thing” is all you need’ considered harmful
• jtrn 4mo ago
  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.
  • nezi 4mo ago
    The long live x is a lazy meme that draws attention that posters can use to skip thinking of an actual appropriate title.
  • theahura 4mo ago
    that is a better title! Added it as a subheader
• IceHegel 4mo ago
  Funny, now it's the management saying "Go be a bohemian, experiment, spend freely." and the employee saying, "Hold on, where's my ROI?"
• kaizenite 4mo ago
  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.
• mvkel 4mo ago
  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.
  • leptons 4mo ago
    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.
  • denkmoon 4mo ago
    Without a doubt this too will be overbuilt. At least we’ll have cheap second hand DC gpus in however many years.
• EGreg 4mo ago
  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?
  • theahura 4mo ago
    (its in the article, which predicts that there will be another round of tokenmaxxing with different underlying incentives)
  • Sharlin 4mo ago
    It's actually used properly here.
• et1337 4mo ago
  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.
  • seattle_spring 4mo ago
    > 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?
    • rezonant 4mo ago
      Isn't that like a day worth of tokens?
      • codegladiator 4mo ago
        10 days
  • jdiff 4mo ago
    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.
    • RugnirViking 4mo ago
      this! the back-and-forth chat interface where you can edit only your own messages, and only then to get a new response, is a terrible one, but I think favored by vendors because it helps them fight in vain against prompt injection. Custom harnesses and stuff are nice but incredibly time consuming to set up when all I want to do is like, see what the agent is reading, and editing out some irelevant nonsense side quest it went on, or trim some massive log file it read which filled 90% of its context. Theres no inherent reason behind some caching gains that these things must be strictly chronological - a response it gave me previously does not have to be part of the context now
• red_admiral 4mo ago
  > 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.
  • VulgarExigency 4mo ago
    It's astounding to me that they looked at Second Life and really thought that was the future.
    • deleted 4mo ago
      [deleted]
    • DaSHacka 4mo ago
      I could easily see that being the case, which is why I was so against it. I think they're just a few decades too early. Similar to cloud gaming, although that's much closer on the horizon.
    • Izkata 4mo ago
      I remember there being a lot of phrasing in the announcements that implied they didn't know Second Life existed. Kinda seemed like they thought it was a completely new idea.
• dofm 4mo ago
  This is like hell, if hell was being stuck on a really poorly-maintained uncomfortable rollercoaster forever.
• natyoung 4mo ago
  Studies have proved that you'd have been better off with fartmaxxing.
  • watt 4mo ago
    I have no doubt those studies are run by some smart fellers.
• ambicapter 4mo ago
  > 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.
  • NateEag 4mo ago
    > This take is so weird I suspect author somehow financially benefits from tokenmaxxing. They might own a chunk of NVDA.
  • baddash 4mo ago
    it's a huge oversimplification imo. it reminds me of someone worshipping LOC: more = better
  • manicennui 4mo ago
    Did you read the article? "Most teams haven’t yet figured out how to build their own Ramp Inspect or Stripe Minions (if that’s you, reach out — we can help!) but basically everyone is at least using cursor in the side bar."
    • noodletheworld 4mo ago
      ? What is your point? That the OP is obviously finically motived to encourage tokenmaxing? Here’s what they said, $$$ aside: > 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 > Compounding correctness flips the calculus. If more token spend leads to better outcomes, then you’re going to want to spend a lot of time running tokens. Which sure as hell sounds like tokenmaxxing to me! The original incentives to tokenmax are gone, but eventually folks will realize that a new and more powerful incentive has take its place. > There were ways to get loops to work, but it was hard. You had to think a lot about how to prompt the agent, which in turn required a pretty deep familiarity with how these things work. > Now, though, it’s easy. Compounding correctness makes it easy Go on, tell me I’m quoting the OP out of context. It’s pretty clear this person believes in compounding correctness, while other, more serious people (1) are perhaps more skeptical. ..and Armins company owns pi. You can’t get much more all in on AI. Compounding correctness sounds cool, but the real examples of people spending lots of tokens are not compounding correctness; they are wide parallel exploration; like Mythos. The OP is confused, and wrong; they’ve made some basic (flawed) assumptions, and based their entire reasoning on them. …and are selling AI things. How surprising. [1] - https://lucumr.pocoo.org/2026/6/23/the-coming-loop/ https://lucumr.pocoo.org/2026/6/23/the-coming-loop/
• gmziven 4mo ago
  [dead]
• chaboud 4mo ago
  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.
• m3kw9 4mo ago
  If you are really engineering, you would really be tokenoptimizing for most quality per token.
• GeoAtreides 4mo ago
  cute easter egg on the story points showcase :)
• koiueo 4mo ago
  > Compounding correctness flips the calculus. If more token spend leads to better outcomes Citation needed
• thousandflowers 4mo ago
  The thing that most disconcerts me isn't the runtime pruning, it's the cold loading. Months ago, I added a few skills and MCPs to test them, partly in the frenzy of free shopping, but then I forgot about half of them. So after I got tired of choosing by hand, and therefore also a bit blindly, I created a small tool that runs locally and analyzes conversations to tell you which skills, MCPs, or other things are always unused. 347 items never used · ~19354 dead tokens/session · ~$25.49/month A lot of ECC that I never used but always loaded. If anyone's interested, I've put it on GitHub, thousandflowers/skillreaper.
  • thousandflowers 4mo ago
    [dead]
  • Kiog-Aser 4mo ago
    [flagged]
• San-Jose 4mo ago
  [dead]
• ElenaDaibunny 4mo ago
  i think tokenmaxxing mostly comes from cloud pricing. once you're paying by the token, you naturally start caring about token counts. with local inference i barely think about it anymore.
• fabijanbajo 4mo ago
  [dead]
• manicennui 4mo ago
  This is little more than an ad for their services.
• tatsuya-tamaya 4mo ago
  [flagged]
• deleted 4mo ago
  [deleted]
• adammcdaniel 4mo ago
  I was one of those mentioning the death of tokenmaxxing (https://www.ibm.com/think/insights/tokenmaxxing-dead-long-live-valuemaxxing https://www.ibm.com/think/insights/tokenmaxxing-dead-long-li...) I would say tokenmaxxing = spending without limits or care about results (and assuming results). The term as it is right now, at least. When it comes to "using tokens overall", then open source models change the equation and in that case, we will enter a phase of 'maximizing AI usage...but for near-zero marginal increase in costs with increased usage'. But even then, the convo would shift to platform engineering...which would then ask 'what value are we getting out of this?' OR - cloud model economics change over time and we use cloud models as happily and cost effectively as we do cloud storage now. But hard to say when that comes. Open to thoughts, though.