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  • Hacker News
  • >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.

  • 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."

  • > database servers are Swiss city names, web servers are Denmark, storage is Finland

    consider me officially triggered

  • I'm also taken aback with how naive folks are about companies, they really seem to have bought the whole "capitalism is efficient" maxim hook, line, and sinker.

    I really struggle to imagine how anyone in a corporate environment has managed to never run into obvious examples of waste like you describe (overpaid consultants and mandatory budgets are classic examples). Office Space came out 27 years ago and has a plotline making fun of overpaid "efficiency consultants" whose only job is to tell management to fire people.

  • 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.
  • What is meant by a "loop" here? Just repeating the same prompt until you get the desired result? Are subsequent repetitions too close to each other?
  • > Just repeating the same prompt ...

    If you were tokenmaxxing you would understand.

  • > 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

  • Loop "engineering" has now become a thing now apparently (a la prompt "engineering") https://github.com/topics/loop-engineering
  • Tokenmaxxing was never a thing to begin with. Just because a few companies did it doesn't mean it was a widespread phenomenon.
  • The issue is the companies doing it could spend billions on tokens and they have. I for one know that there are multiple Big Tech Fortune 500 companies that have burnt over 1B in tokens in a single quarter.

    This is purely for coding and analogues.

  • Agreed. There is way too much noise made out of this from a handful of companies.
  • 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.

  • > 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

  • 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.
  • This is like hell, if hell was being stuck on a really poorly-maintained uncomfortable rollercoaster forever.
    by dofm
  • 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.

    by jtrn
  • that is a better title! Added it as a subheader
  • The long live x is a lazy meme that draws attention that posters can use to skip thinking of an actual appropriate title.
    by nezi
  • 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

  • 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.

  • > 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.

  • 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.

  • > 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.

  • 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.

  • 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.
  • 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".

  • > 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.