Companies rein in AI usage as costs strain budgets
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There's a lot of issues, ranging over technical, cultural, environmental, and moral problems. But there's also obvious value. To say otherwise tells me you haven't actually tried to make use of these tools.
It's one thing to get an AI google response and feel like it's dubious, it's another thing to know what you want and have an LLM find the APIs for a framework you're not familiar with yet and put the pieces together. The only way I use AI for programming still involves a large amount of rejecting the responses and a massive amount of reading and validating.
Am I able to write things faster with LLMs, yes. Am I missing out on the work involved in learning things I would be forced to otherwise, also yes. Are coworkers pushing stuff they don't understand more, surely.
It's a mixed bag, and we need more balanced takes in the discussion around this.
Nuance simply gets overwhelmed by repetition.
The most recent opinion forming narrarive Ive been seeing repeated endlessly on this topic is about some supposed "split" in programmers between those who "enjoy the process" and those who "want the outcome".
It is very carefully designed to miss the point and is some quite clever propaganda - it presupposes that the outcome is the same without directly stating it and implies that skeptics are dinosaurs without needing to be too direct about it.
There are fake accounts pushing AI everywhere, and people burned out by the marketing that react positioning too aggressively in the opposite direction (particularly when it's their boss who bought into the marketing and makes unreasonable demands).
There's also a lot of ideological opposition, which often tries to claim that the tech is useless etc.
> Am I missing out on the work involved in learning things I would be forced to otherwise, also yes.
Yes, but many of those things are things you might not really care about learning about. And if you want to learn about them, AI can be a big help, if you use it appropriately.
The "mixed bag" comes from the way people use it, mostly not from the tech itself.
The naked display of the elites willing to fuck over large swaths of Americans is not only despicable it is in our civic duty to rightfully fight and reject this.
No one wants this yet it is being thrusted upon us and we are forced to pay for this madness. If you ask most Americans they would probably be completely okay with nationalizing big tech or seizing their assets.
Why does this tech have to champion naked displays of greed where the elites feign surprise that people are willing to fight for their lives?
This is the single issue that unites Americans across parties, incomes, and race; it's the class issue of the century and the people yearn for material change.
What did I get wrong exactly?
What I pointed out is that ideological objectors often try to claim that AI is actually technically useless.
The problem with that is that it makes their arguments seem less credible, and even misleads their own supporters into underestimating what they’re dealing with. It’s a literally self-defeating position.
LLM is great at identifying useless writing - if you have llm writing it, it should not exist.
What I'm hearing is that the 0.00001% use case is great while the 99.9999% use case is shit--and we're supposed to think that's reasonable.
Feeding nonsense to pretty much the entire population is just fine with tech bros because a few programmers have an easier time cranking out some code to more effectively sell ads?
That's not a mixed bag, friend. That's a bag of horse shit with one M&M at the bottom.
Like I said, if you can't see the value in AI, I'd hedge a bet you haven't tried. Even a brief conversation with google's can help identify a gap in your understanding of many topics.
How we balance the positives with the negatives is the hard part I want to hear thoughtful and studied opinions on.
Why would you try to make use of these tools when there are obvious environmental and moral problems with them? What do you tell yourself about those problems, and how do you get past them?
4 dependents, a cost of living that keeps rocketing and an industry that’s decided “the people who don’t glaze this shit don’t get to continue”.
Maybe Ive sold out but what’s the alternative, I’m 17 years in, I can’t figure how I pivot my expertise and still support the family’s demands.
But the OP didn't sound like one of the reluctant.
There was a good moment where I thought it wouldn’t come for my org but here I am.
Not saying the tech doesn’t have merit but if you’re not blasting the slop cannon constantly and praising Dario for the pleasure, you’re on the list.
We don't solve the climate crisis by abandoning all the technological progress which has put such a strain on our ecosystem, we solve it by rethinking how we use this technology, and finding new technologies and policies to better meet our needs.
There's a significant difference between understanding a technology and using a technology. We can understand how a technology is made without totally changing our workflows to rely on it essentially.
How many cities do we have to blow up to understand nuclear weapons? That's a serious question, because atomic bombs were dropped on both Hiroshima and Nagasaki.
> We don't solve the climate crisis by abandoning all the technological progress which has put such a strain on our ecosystem, we solve it by rethinking how we use this technology
I don't think that's true. Shouldn't we abandon fossil fuels? Switch to cleaner energy, solar, wind, geothermal, electric cars, etc.?
The analysis that I want is on a studied cost/value basis somehow. I'd start by trying to force tech companies to sell products at cost sooner, so it's not driving markets before it can truly be absorbed. I'd also ask for energy/resource consumers to be forced to buy climate credits which are used to help offset the impacts and fund research and development for sustainable technology.
> The analysis that I want is on a studied cost/value basis somehow.
If something is immoral, do the ends justify the means? I would reiterate that you originally mentioned moral problems.
> I'd start by trying to force tech companies to sell products at cost sooner, so it's not driving markets before it can truly be absorbed.
That sounds an awful lot like abolishing capitalism. Which might actually help with the climate crisis, regardless of AI.
> climate credits
These always seemed like BS to me, a way for wealthy corporations to buy their way out of doing anything.
Absolutely. The AI ROI question is the entire ballgame. Earlier today I heard the term "jagged technology" for the first time, and it's an extremely good one. Given how jagged AI appears to be, anecdotal reports are all over the place. It also doesn't help that it appears heavily using this technology can affect people psychologically. The information environment for someone who wants to know what this tool is good for and what it isn't is.. treacherous. Some clear, objective grounding would really help.
You can stop right there. Whatever we’re doing to prevent global disaster from new technologies is not working.
Morality wise, it might have “obvious value” to poison my competitors and steal from my business partners, employees, and customers. That doesn’t mean I am obligated to “try to make use of these tools.”
The issue is not that AIs are useless. It's that they are objectively worse at the job (except apparently programming[1]), than a cheaper, entry-level worker on their first week still learning how to do the job, even though nearly a trillion dollars has been spent on them by this point. The worker gets substantially better over time, and slightly more expensive. LLM models get slightly better over time, but substantially more expensive.
[1] The output of even the latest models would have gotten a junior programmer PIP'd back when I was still programming many years ago. That is now considered to be above average code quality is a disheartening referendum on how bad programming standards have fallen since then.
At the current, VC-subsidized price point, sure. But at the real market cost at which the AI companies would break even on their offerings, the junior is cheaper and more effective than Claude within about 3 months. And to be blunt, if that's not the case then the kind of programming you do is already basically junior-level development anyways and it's a waste to have seniors handing the role that could and should be handled by juniors.
To sum it all up, there are good arguments both for and against AI, but it increasingly feels like it's ideologically driven and feeds into delusions.
Not only that, but while the technology itself isn't inherently evil, you can leave it up to humanity to absolutely misuse it - together with unregulated capitalism, it results in one big mess.
So even if in say 100 person engineering out 10 folks might get 2-3x critical path work. 50 folks Might just add non-critical path work, and the other forty might use it in a way that they end up doing g less critical path work.
But depending on your metrics productivity could look up while the bottom line is unaffected. In which case model quality is a red herring.
We’re not innocent bystanders here, and it’s important to recognize that. Our hype added to the hype. Our optimism added to the optimism. After layoffs due to Section 172 and interest rates going up, technologists were looking for a reason to be in-demand again, and generative AI as a platform specialization provided that.
We can’t now criticize CEOs for being taken in by the same enthusiasm we pushed for our own purposes.
CEOs are very well compensated for the things they do. If they were led astray by snake oil salesman that does not make Hacker News as a community complicit. They were fooled when they shouldn’t have been and it’s their own fault.
Also, I'm genuinely excited about AI. It's absolutely incredible. Even with all the problems, I'm more invigorated about being a programmer than at almost any point in my career. You have to embrace the chaos.
Many of us were skeptical from the start, and have done nothing to hype up LLMs.
Are these CEOs the "very smart people" you're talking about? To my eyes it's mostly the same crowd that was drooling over crypto and blockchain and the metaverse just a few years ago, and it was clear that was a stupid idea at the time too.
It's all boils down to the same problem: A smart programmer who enjoys optimizing something that's not on the hot path: developer velocity.
Lol.
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.
The impact of AI on jobs appears to be more in terms of hiring slowdowns: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5425555
> Following adoption, junior employment declines in adopting firms relative to non-adopters, while senior employment trends remain largely unchanged. This decline is concentrated in occupations most exposed to GenAI and is driven primarily by slower hiring rather than increased separations.
It's that enough execs think it can happen.
No actual evidence is required for that.
But I've started to deliberately constrain myself because of what you describe. Sure, I'm not convinced that it actually come to fruition, but just the realization that this is what they're daydreaming about makes me sick so I've forced myself to only do the bare minimum or less now.
The value is somewhere else (i.e. being able to brag at the next conference/dinner/awards show and to not feel like a loser)
Once that value is no longer there, I will stock up on popcorn. Sure Labubus are still around and still have "users", but...
$1k/month is nothing as a hedge against a CEO being accused of causing their company to be left behind in the AI utopia of tomorrow. If you’re in a peer group that rewards risk taking and all of your peers are taking a risk, you’ve got to take that risk too. Better to burn money trying something and then failing, than to not try. Failure is acceptable, missing an opportunity is not.
https://xcancel.com/eastdakota/status/2025221270061580453
“My advice: don’t be a [dinosaur]. I’ve seen this movie before and they go extinct. ”
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.
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?
The moment you have Claude Code or Codex running in a loop - or in multiple streams (something that people don't really do with chat because it returns fast enough there's no point running them in parallel) your token usage goes through the roof.
And then by May this year both OpenAI and Anthropic had migrated their enterprise pricing to API costs, not fixed subscription per month costs. That wouldn't have made much of a difference in the pre-coding-agent era, but today it means $100s or $1000s per employee per month.
I figure we’ll go from over usage to a shock leading to under usage and then land somewhere in the middle when companies decide what works for them.
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.
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.
Groupthink. FOMO. Envy. Hubris. Greed. Those fuel Big Tech and we get to pay for the results.
If I made a blunder of that scale, would I or would I not be put on a PIP?
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.
Critical times thinking is considered ineffectivity last 30 years or so. Managers who do that are considered bad.
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
- 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.
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.
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.
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?
it was before ChatGPT
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.
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.
I am seeing people use it to write emails and messages on IM lol
People with existing skills can supercharger their dev output with AI. But it looks like everyone just goes up for vibe coding
It's too useful to ignore, but too expensive to pay-as-you-go at current pricing for frontier models. Smaller, less capitalized companies will use the subscriptions (if they still exist by then), and larger firms will just build out their own compute for their dev teams.
I’ve got screenshots from months ago telling people exactly this stuff would be reported in the coming months. Just funny to watch really. I’m more convinced than ever you cannot trust most people - you must think for yourself and most people are stupid.