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- Hacker News
- I knew this was going to be the end result after seeing so many companies reward employees based on how many tokens they were using. My company even pulled stats and gave physical awards out at an in person retreat. Ridiculous, and it was never going to last.by Trasmatta
- I remember back when ChatGPT first came out, there was an article on HN about this AI researcher who worked for one of the big companies (I think Google) who came to believe the model was truly intelligent and that it was being abused by being locked in the machine. We all laughed as the guy had clearly lost his mind to AI psychosis. What we didn’t realize is he may have been patient zero.
This is the delusion that went viral, or at least one version of it. It all leads back hijacking the human tendency to anthropomorphize, leading to the belief that an LLM is somehow something more than it actually is. So the question is - what breaks the spell? Failed attempts to automate that don’t work out? The realization that the return on money spent doesn’t make sense? Furthermore, how to we accelerate the eventual realization?
by IAmGraydon - I talked to a former coworker recently and he kept gendering Claude, which felt really, really weird to me. And this guy is probably one of the best data people I've ever worked with.
It's a really strange time in that I use a bunch of AI and am really excited about the product capabilities, and yet I feel way less AI pilled than all my friends and coworkers.
- > what breaks the spell?
If throwing more compute at the problem keeps only resulting in incremental gains, I think that should do it. It goes one of 2 ways, really. Either we can throw enough compute at pre-training that results in infinitely more capable models to the point that the cost is now justified [1], or, we hit a scaling wall, get stuck with what we have now (or at that time) and the valuations crash knowing that "this is it" for the foreseeable future without a big breakthrough.
The labs go bankrupt or get acquired by the typical giants (Google, Microsoft, Amazon), the models get rolled into GCP, Azure, and AWS as a service, and that's it. It becomes another dev tool, much like a new IDE.
[1] cost being justified I'd rank as "your average non technical PM can now end to end develop robust, production software free of most serious vulnerabilities." model & tool capabilities that would allow you to hire a small team of non-techincal roles, for half the salary, that can produce the output of a large engineering org. If that doesn't happen, I don't see how the current buildout is sustainable.
by thewebguyd - https://www.scientificamerican.com/article/google-engineer-c...
it was before ChatGPT
by progval - Does anyone know the inside story of some of these AI adoptions that have been downsized? The company I’m at has only only recently gotten an enterprise license.by le-mark
- I know about a small company with literal competition about who spends more tokens. They had a prize for winner - not too big materially but a lot of status attached.
The competition remained after switch to token pricing and abruptly stopped at seemingly random moment.
Frankly, I want competition about who finds the most expensive work trip hotel.
by watwut - Company is a fortune 100 and a client of mine.
Since the switch to API pricing they’ve cut usage limits in half twice and are now saying that anyone with high usage is essentially going to be audited.
They’re down to about 500 a month per person.
by ofjcihen - Probably looks like this:
- teams blitz through Jira tickets
- developers figure out they can't keep up with reviewing the code
- too many new features pushed at once, rushed work to develop training materials
- features don't work as good, many edge cases come out in support tickets
- tickers return to Jira board
- teams spend time triaging and fixing with less AI
- some features turned out to be mistake, but now have to stay
- once mess is cleared, return to "normal" pace, no AI agents, Cursor allowed with budget cap.
by varispeed - We’ve had our AI budget per Engineer cut twice now since the peak mania in early 2026 and Fable was banned even before it was removed by Anthropic due to cost. It’s still used a lot but I think maybe they’re not really seeing the ROI especially when some people spent thousands and thousands per month on dubious AI things.
Personally I truly can’t manage that many tasks (really 1 or 2 max) in parallel with these since you need to think very hard about everything the AI spits out because they’re such natural bullshitters and you end up in places where no one on the team understands anything in the project
by coffeebeqn - by sirnicolaz
- If your choices are “reduce productivity, make money” or “increase productivity, but still make the same money”, why would you ever choose the latter?
The thing about option 1 is that you still have “potential productivity” that you can tap into during critical times, where as in option 2, employees have already used up the “potential productivity” doing god knows what with AI, and you can’t push them more without breaking.
by deadbabe - > potential productivity” that you can tap into during critical times,
Critical times thinking is considered ineffectivity last 30 years or so. Managers who do that are considered bad.
by watwut - CEOs laid people off to replace them with AI, but turns out AI is more expensive and does a worse job.
If I made a blunder of that scale, would I or would I not be put on a PIP?
by noncoml - CEOs generally suffer zero consequences for their decisions, unless that decision costs someone real money.by etchalon
- I genuinely have no idea how some of these companies got so far over their skis on AI. It simply does not make sense to me.by sroerick
- Simple answer is that these execs live in a big bubble and goad each other into bigger and bigger investments via groupthink.by afavour
- Apple and Meta (and others) did the same thing with VR. In 2015 all these CEOs were looking for their next app store and, herd-like, settled on VR computing. They couldn't come up with anything more promising so they burned tens of billions on failed goggles that anyone with any sense could have told you was never going to work.
Groupthink. FOMO. Envy. Hubris. Greed. Those fuel Big Tech and we get to pay for the results.
by asadotzler - IMHO it’s just good old fomo. They fear that the landscape will shift overnight and they’ll be left with a ton of useless meat bags instead of a pay as you go models that you can upgrade instantly every quarter.by prymitive
- Out of touch leadership and management combined with a culture of self-congratulatory "innovation" where companies just plagiarize eachother in an endless loop... It doesn't surprise me at all, tbh.by jcgrillo
- They believed and were financially incentivized to embrace the hype and operationalized it because technical leadership thought rapid PoCs would apply to the rest of the tech stack.by taurath
- I'm consistently burning over $100/day in Claude/OpenAI tokens using Codex and Claude - but I'm on the subscriptions so I'm only paying $100/month to each vendor.
If I worked for a larger company that isn't allowed to use those subscriptions and has to pay list price I'd be costing them ~$2,000/month. Now times that by a large engineering team.
by simonw - > The ride-hailing company has introduced usage caps, limiting employees to $1,500 in monthly token spending on individual AI tools, after blowing through its entire AI 2026 budget by April.
Right, because they set their 2026 budget in 2025. And in 2025 nobody could predict how good (and token-hungry) coding agents would get after November 2025.
I'd be surprised if any company that set an AI budget for 2026 hasn't blown through it by now, assuming their staff have picked up Claude Code or Copilot or Cowork.
by simonw - A CEO unable to predict or even imagine a few months down the road, who bets everything on the current state of things, is a shitty CEO.by asadotzler
- If they were getting something in return (financially) they’d have no problem expanding the budget even.
You seem to be desperate. What’s wrong? Finding it hard to believe that you can have all this intelligence but it can make the firm financially worse off? Haha.
by 1eieies - I think this probably has more to do with companies switching to API pricing for enterprises, no?
Regardless, the C-suite wouldn’t be performing due diligence if they weren’t at least attempting to perform the calculus of “what are we getting out of this spend?” and what we’re seeing now is them looking for the justification.
Didn’t Uber mention that they’re having a hard time tying all of that spend to any new or improved features?
by ofjcihen - Companies are learning that even with mass layoffs, AI isn't worth what it costs for most use cases. This is an important inflection point because none of the AI companies are profitable, i.e. they're all still charging substantially less than what it costs to actually deliver the service. With things in that intermediate state, it's hard to know what a future stable state will be like.
- If AI isn't worth what it costs why are some of these companies allowing $1,000+/employee/month?by simonw
- > Since the start of the year, Chinese AI models have overtaken their US counterparts in token consumption, according to data from OpenRouter, an aggregation platform that allows users to access multiple AI models.
That's a bit of a dodgy statistic. OpenRouter only tracks their own users - the vast majority of API customers for OpenAI and Anthropic presumably go straight to their APIs.
by simonw - It's true that OpenRouter may be a biased sample - however, do we have reason to think that isn't a relatively stable biased sample? If not, then the trendline in OpenRouter usage is still pretty interesting.by anon373839