4 ms·

AI sticker shock hits corporate America

172 points by 1vuio0pswjnm7 5mo ago

cynicalsecurity 5mo ago
> Instead, they should focus on using AI to drive revenue. There is a complete disconnect between wages of employees and company's revenue => Why aren't employees working towards revenue? What a mystery. Children, let's help Elmo solve this mystery. And then random mass layoffs to make numbers for shareholders look great in quarterly reports. Surely this motivates people work to their fullest potential and to care for company's revenue.
- roxolotl 5mo ago
  Even better there’s a complete disconnect between revenues and metrics we use to measure productivity. Corporate wants to believe there’s numbers you can use to measure knowledge workers like widget makers where there’s really not much that’s effective beyond revenue.
- mapontosevenths 5mo ago
  I found this claim interesting so I looked into it. Everything I can find shows that the intuition is accurate. Companies with EOSP programs outperform those that do not in the market by about 17%.[0] Companies that perform layoffs, despite short-term stock boosts, underperform on a period of years showing a 14% decline in their Return on Assets (ROA) in the years following the layoffs.[1] [0] https://www.nceo.org/employee-ownership-blog/new-study-shows-esop-company-stock-prices-outperformed-market-indices https://www.nceo.org/employee-ownership-blog/new-study-shows... [1] https://www.researchgate.net/publication/277473996_Financial_consequences_of_employment-change_decisions_in_major_US_corporations https://www.researchgate.net/publication/277473996_Financial...
Spide_r 5mo ago
https://archive.is/crTG8 https://archive.is/crTG8
CuriouslyC 5mo ago
This is almost entirely on Anthropic and the stupid C suite people trying to push TokenMaxxing. GPT5.5 is much more token efficient, other models are much cheaper, and if used in moderation rather than than trying to get everyone to OpenClaw 24/7 with token leaderboards, it's much more economical. Also ironically, a lot of GenZ and young Millenials who were already bitter at their employers have used the tokenmaxxing push to sabotage the AI rollouts by burning tokens on stupid shit. It seems to be working.
- kleiba2 5mo ago
  Citation needed.
- throwatdem12311 5mo ago
  I’m an “old millenial” and the excessive burning of tokens will continue until working conditions improve.
  - voidfunc 5mo ago
    Working conditions are fine, I simply am not incentivized to be efficient with tokens.
    - throwatdem12311 5mo ago
      Yeah, everything is fine until you don’t want to use AI for something because it sucks at that task and then you end up on a PiP because your token burn is low. Why the f*ck are AI Token Use Leaderboards even a thing. Features that used to take months are now expected in days. Oh you didn’t merge 40 pull requests and deploy to prod 15 times today? Aren’t you using Opus the greatest thing since the invention of the wheel?! What do you mean it’s hard to review 100 merge requests per day? Just have Claude review it! That’s a PiP. Oh prod is down because people keep deploying code that nobody even freakin’ read? Just have Claude fix it! What do you mean it’s doesn’t work well? Just burn more tokens or you’re on a PiP. Surely there wouldn’t be malicious compliance by people that would prefer to use the right tool for the job instead of having this crap shoved down our throats by management by threat of termination.
Arodex 5mo ago
>Corporate leaders are starting to question whether soaring AI spending is delivering meaningful returns. We should start to question whether soaring CEO salary spending is delivering meaningful results.
- utopiah 5mo ago
  Ah, that's not how it works : CEOs are rich so they are successful. They are successful so they are rich. Q.E.D.
  - hatefulheart 5mo ago
    Maybe in your fantasy world. In reality people are rarely rich based on merit alone. EDIT: Sorry it was a really clever joke.
    - spacechild1 5mo ago
      I think you missed the joke.
    - yulker 5mo ago
      It's sarcasm, obviously.
    - asdfasvea 5mo ago
      >>>EDIT: Sorry it was a really clever joke. I sincerely hope that was your attempt at sarcasm.
      - raffael_de 5mo ago
        exactly my thought.
  - aleph_minus_one 5mo ago
    > CEOs are rich so they are successful. "Successful" in which sense? The most reasonable definition "Successful in convincing other people to give them money" is rather a tautology. :-) A very related problem concerning your argument is well-known for decades: the Principal–agent problem: > https://en.wikipedia.org/wiki/Principal%E2%80%93agent_problem https://en.wikipedia.org/wiki/Principal%E2%80%93agent_proble... It says that the self-interest of an agent (e.g. the CEO) is not identical to the interests of the principal (e.g. the shareholders). Why do I mention this? The CEO being rich is a measurement of the financial success of the agent, but not of the principal. You are rather interested in measuring the success of the principal.
Arodex 5mo ago
Just a week ago, Anthropic barely breaking even was hailed as AI companies being close to profitability much earlier than forecast. In fact it is all smoke and mirrors, pure mania from C-level executives out of their depth trying to one-up each other with company money, and they aren't even close.
- mrweasel 5mo ago
  I didn't look into the numbers myself, but Ed Zitron claimed in his podcast that the only reason Anthropic looks sort of profitable was due to some rather clever accounting (not illegal) and a spending that didn't happen, I think. Things haven't actually improved much, but if you zoom into a very selective part of the fiscal year it looks promissing. https://www.iheart.com/podcast/1119-better-offline-150284547/episode/monologue-anthropic-is-not-profitable-unless-334441675/ https://www.iheart.com/podcast/1119-better-offline-150284547...
- croes 5mo ago
  They become profitable but on the expense of fools like that company.
cmiles8 5mo ago
Playing out in company after company right now: CEOs: “Get me some of that GenAI” CTO: “OK, we have all the GenAI” CEOs: “Employees, it’s AI or bust” Employees: Tokenmax CFO: “Um, this is costing a ton and we’re not seeing savings or efficiency materialize.” CEO: “Are we getting any value out of this?” COO: “Not really, and frankly I’m getting annoyed at all the AI slop turning up all over.” CEO: “OK, well, let’s do a big layoff and then I’ll just say it was because of AI. Hopefully folks won’t blame me for the mess and I’ll just talk about how amazing AI is.”
- utopiah 5mo ago
  > Hopefully folks won’t blame me for the mess Lesson #1 from business school : take all credits, put the blame on others, if there no easy scapegoat blame the "economical context" Lesson #2 and beyond : just see lesson #1, it's enough. You've made it and it's ALL thanks to this amazing business school degree you got, now go profits with your new already wealthy peers.
  - randusername 5mo ago
    I have a literal ledger tracking the number of times executives have used the phrase "evolving capital markets" It's amazing to me how subtle the difference can be between a business leader that seems to know what they're doing and one that clearly does not. Same words, even, but from one mouth it's compressing a complex thought and from another it's word salad to give the appearance of complex thought.
    - utopiah 5mo ago
      Regurgitating word salad coming from Harvard Business Review or whatever publication is trendy at the moment. Indeed the "worst" part is that the initial concept might very well make sense, even be grounded in actual research. Masters of semblance.
- jillesvangurp 5mo ago
  These are golden times for AI consulting. We're getting into that business because it is up for grabs. Everybody as AI FOMO right now and begging people to take their money. Exactly what you are highlighting. And, yet, nobody has the beginning of a clue what to do or how to do stuff with AI. That's classic consulting territory. My analysis of the whole space is that all the tech people are focused on completely the wrong end of the problem space (model quality, training, token cost, etc.). They are geeking out on that stuff. Worse, they are mostly not even that good at using their own tools. I regularly talk to so called "AI native" companies that are hiring enterprise sales people to do sales like it's 2006 instead of 2026. Their product is AI native, but their companies aren't. The real issues are on the low level plumbing end. How do you connect all the data silos you have. Are they even the right silos still? And once you fix that: how do you get organized around tapping into those. What guardrails do you need? How do you deal with compliance issues? Etc. You don't need to do a lot to get value back. Most people haven't gone there yet. Mostly people actually already have and pay for the tools that would enable a lot more if only they knew how: ChatGPT, Codex, Manus, Perlexity Computer, Claude CoWork, etc. What you are outlining is funny but true. The issue isn't money or tools but figuring out what to do with the tools you already bought.
swader999 5mo ago
"An AI consultant tells Axios one of their clients recently spent half a billion dollars in a single month after failing to put usage limits on Claude licenses for employees." Like physically, how could this even happen?
- pjc50 5mo ago
  Agents. An agent is a system for spinning up processes that use tokens, talking to other processes that use tokens. I wonder how many megawatts that waste represented. Just one guy, worse than a small air force of private jets.
- layer8 5mo ago
  This could happen with a large number of integrations or agent swarms working 24/7 with high throughput and long contexts.
- ludicrousdispla 5mo ago
  Maybe the AI consultant gets a cut of that half billion?
- spacechild1 5mo ago
  Let's not forget about the environmental impacts. It's crazy that people are willfully burning so much energy for almost no return. And we thought bitcoin was bad... This is just completely irresponsible, if not sociopathic behavior.
  - slfnflctd 5mo ago
    Bitcoin doesn't have long conversations with you, including deeply technical ones, in a way that you thought only a human being could just 5 years ago. They are not the same. I agree fully with you on the potential for energy waste. We always do that, though, with nearly everything. How many of today's jet plane flights really needed to happen? The question is how much value people feel they're getting. People are having a whole lot more feelings about AI than they ever could about cryptocurrencies, and that train aint stoppin'.
autoexec 5mo ago
Just wait until companies are dependent on on it. When their employees can't think without it. When their AI generated codebase is such a mess they'd need a rewrite to understand it without AI. When they've got AI embedded in all their internal processes and tools. Then massive price hikes will come because they've been bent over a barrel and they'll have no alternative that isn't at least as painful in the short-term as letting the AI company fuck them. The long term won't matter then because any company capable of seeing past the short term wouldn't let themselves get into that position in the first place.
- irishcoffee 5mo ago
  [dead]
lelanthran 5mo ago
I am Jack's total lack of surprise :-/
- dylan604 5mo ago
  How much longer before we get to the “I get cancer. I kill Jack” stage? Isn’t uncontrolled growth a sign of cancer? Or is it more virus like where it just continues to grow without ever reaching a balance with its surroundings?
  - andai 5mo ago
    >declare war on natural ecosystem >win
Balinares 5mo ago
Overheard recently: "Thanks to AI we're producing more code and more MRs, faster than ever, but the milestones aren't getting hit any sooner. Actually the opposite, if anything." I wonder how widespread that phenomenon is. Perhaps it's no wonder the prominent actors are trying to rush to IPO...
- FerretFred 5mo ago
  Was that at Microsoft by any chance?
- mapontosevenths 5mo ago
  Goodharts law. The metrics were always measuring the wrong thing, and now that we've finally optimized for the wrong thing successfully management will be forced to admit it and move on to another, slightly different, metric that doesn't actually equate to shareholder value. It doesn't matter what the line actually measures, just that it goes up.
- whobre 5mo ago
  That's exactly what's happening. Many claim they are more productive with AI, but individual rise in productivity just doesn't translate to projects being completed any sooner. And by "projects", I mean corporate ones with big teams involved. Hobby projects actually do get finished much faster.
  - nijave 5mo ago
    In the corporate world, writing code was always a small chunk anyway. Iirc something like 30% of employee time. Getting 50% faster there still only gains back 10% of your time. To further complicate matters, you had to spend on AI software and potentially additional on legal/risk/security/compliance to enable that. The smaller the company, the bigger that % of coding is of total time (all the way down to hobby where the majority of time is spent coding)
    - ryandrake 5mo ago
      Where I work, I would guess that, out of the amount of person-hours spent on a project, less than 5% of it is the cumulative time spent designing and writing code. There's so much other stuff going on: Requirements gathering, "aligning" with other teams, human reviews, QA, presenting to executives, waiting for approval from executives, reporting status, deploying to staging, internal dogfooding, slow ramp-ups to production... This is how projects that are 50 lines of code take 3 months to deploy. AI is helping reduce the time spent on that 2%.
mystraline 5mo ago
Well, if AI has a massive sticker shock attributed, so we should target the high value roles and should save money, right? So im looking at CEO, CTO, CFO, and all the chief-something-officer. If LLMs are that totally amazing at thinking, then we should be targeting upper management, not the workers. That would save a LOT of money for the shareholders! /snark We all know why they wont.
- 59percentmore 5mo ago
  So it goes. Wage theft dwarfs the amount lost to street-level theft, robbery, burglary, etc., combined. The economic stimulus from correcting even a portion of annual wage theft would represent complete coverage of those violent thefts - economically-speaking, there would be no reason for criminals to carry them out. Why rob a gas station to get your drug money? Everyone around you is making enough extra at work that bumming a dollar here and there covers it. That sort of thing. But good forbid we actually correct a major social ill at the expense of the people who profit from it.
  - mystraline 5mo ago
    Exactly. And even worse is that crime itself is firmly rooted in politics. Example: You work at walmart, as a cashier. You drop a $100 bill on the floor and pocket it from the till. You're caught, cops called, and you are arrested. Example: You work as a manager at the same walmart. Store manager says labor costs are too damned high. So you go in on 10 employees, and edit their timecards to cut $100 from each of them, totaling $1000. IF you are caught, police will not respond. Instead, it is a "civil matter". This is a bit dated chart, but its still very much correct. https://www.tcworkerscenter.org/2018/09/wage-theft-vs-other-forms-of-theft-in-the-u-s/ https://www.tcworkerscenter.org/2018/09/wage-theft-vs-other-... But notice the wage theft types are all "civil matters", and the non-eage theft are heavily criminally prosecuted. And who does those? Predominantly poorer people. We also see this with dumping trash, being criminal and severe to the individual, but companies (read: Musk) can dump thousands of gallons of toxic sludge per day. https://www.yahoo.com/news/articles/inspection-texas-drainage-ditch-reveals-170629588.html https://www.yahoo.com/news/articles/inspection-texas-drainag... We also see criminality differences between charges of freebase cocaine versus crack cocaine. Crack was what black people smoked, so sentencing was like 10x of freebase. When you start looking at how laws are apllied, its almost always the same pattern: those at the top are a civil matter. Those who report to the top are a criminal matter. Those at the bottom are "charged with the fullest maximum punishment".
ecshafer 5mo ago
>Corporate leaders are starting to question whether soaring AI spending is delivering meaningful returns. This isn't surprising. Ive recently run into quite a few rabbit holes where AI is bad enough that its much more efficient to do it myself. I wanted to refactor some code, gave it a design pattern to go towards, some specific classes and methods, etc. making it a well described problem. AI just couldn't do it satisfactorily. The code was ugly, overly verbose, and after multiple tries with multiple prompts saying to keep things simple. They still would introduce new classes, useless fields, etc.
- chrisweekly 5mo ago
  "AI" is "bad" and "just couldn't do it"? Specifics w model and harness would lend more credence.
  - ecshafer 5mo ago
    This was GPT 5.5 and codex. The specific model and harness isn't that important here. AI could do it. But the issue seems to be that there are some tasks where AI kind of falls over and provides poor results. It was easier, better, and faster for me to just do it myself. I have found a lot of cases where AI is great. If you have a UML diagram already, or translating code from language x to y, fixing unit test failures, generating boiler plate. But I can definitely see if people are using large amounts of AI for writing code, analyzing code, etc. that they are not actually seeing returns.
- new_account_101 5mo ago
  [dead]
imglorp 5mo ago
This is an important inflection point. When tokens get correctly priced, all of the insane over-investment in capital will need to draw back: buying data centers, semiconductors, and politicians. Even then, it won't be right-priced with regard to actual costs. The environmental impact should have been priced in from the beginning. There seems to be a parallel with subsidizing fossil fuels, under pricing them which encourages over dependence, ignoring the real costs society will pay later.
- whazor 5mo ago
  It rather looks like chatgpt/antrophic enterprise tokens and API calls are too expensive. Competition is quite strong on openrouter. However, the real problem is running wild with token burning. With parallel agents calling subagents you can burn lots of tokens per minute. Especially with thousands of engineers.
- somenameforme 5mo ago
  I've yet to see any compelling data about inference being particularly expensive. For local LLM models, that are becoming increasingly viable, it's dirt cheap. The same is also true in image gen world where now even a heavily dated GPU can cheaply and quickly produce high quality images. I also think the image gen world is a useful analog because there are a million sites, presumably still making money, with markups that are multiple orders of magnitude off their costs. They're feeding off user ignorance that was, at least in part, artificially seeded by implying high costs for image gen back in its day. Though it's possible/probable that the initial training runs were expensive, but that's a one-and-done cost.
internet_points 5mo ago
https://www.merriam-webster.com/dictionary/sticker%20shock https://www.merriam-webster.com/dictionary/sticker%20shock oh. i thought it was about people putting up stickers like https://mastodon.social/@spellingmistakescostlives@mastodon.ie/116611777282440254 https://mastodon.social/@spellingmistakescostlives@mastodon....
stockresearcher 5mo ago
We use GH Copilot at work and this week sat for a presentation by GH about optimizing token usage and maximizing ROI on tokens used. Anyone else get this presentation? They didn’t have time for questions because they had to run and give it to the next big enterprise on their list… They basically said that everything is too expensive, you have to watch it like a hawk. It was as if they poured a bucket of cold water on the room. People were wondering how they could do anything faster with all these strategies. And then “sorry no questions. Bye!”
- karmakurtisaani 5mo ago
  We did not have any presentation yet, but the first serious discussion about the cost of tokens has started on the documentation level. Looking forward to seeing these presentations!
- Esophagus4 5mo ago
  Did you have any good tips for optimizing usage? The ones I’ve stumbled upon seem to be: switch models based on task complexity, use tooling like ASTs and compression, disable unused MCPs, compact often, be verbose with input to give clear guidance…
  - deadeye 5mo ago
    I don't think compacting often is good for saving money. It generates more output tokens and then the input is no longer from cache, which is priced differently...typically very differently.
- spaceman_2020 5mo ago
  Just hire people and pay then a fair wage and let everyone get richer together ffs When did American capitalism become such a zero sum game
  - rickydroll 5mo ago
    When the powers that be decided labor didn't matter and the only thing that mattered was capital. One will never get rich on wages. The only way to get rich is through asset manipulation and rent-seeking.
deleted 5mo ago
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TSiege 5mo ago
I really can't tell what is going on with AI these days. I hear AI labs claiming theyre profitable or close to it. I hear companies say they're dubious the juice is worth the squeeze. I've seen anecdotal claims of a measurable increase in productivity of 2x in PRs created and merged coming in at cost 20% of engineering employee budget. Others say they're still getting no value (which I doubt). Simon Willison's recent post went into debunking the AI sticker shock claims somewhat. Either way this seesawing between new golden era and the greatest VC money furnace is becoming exhausting. I'd like to see real numbers at this point, and this article is just a few bullet points that link to other articles. Talk is far cheaper than tokens and I'd like to have a workflow that I can rely on being there in six months. https://simonwillison.net/2026/May/27/product-market-fit/#the-ai-failure-stories-around-this-are-pretty-thin https://simonwillison.net/2026/May/27/product-market-fit/#th...
- bitexploder 5mo ago
  AI Has empowered people to build things much more quickly. Not slop if you are even a little conscientious about how you use it. What it does not do fix the human structural problems. If you are solving the wrong problems you aren’t doing anything useful. Just because you can now take an idea to near completion doesn’t mean it was worth doing, but now you spent tokens and a lot of your mental bandwidth to finish it. Or worse you let it become slop and it will fall apart if you even look at it funny. Previously if I needed to automate something I thought really carefully about it. Now, I still think really carefully about it. I had fun AI coding some tools I always wanted but they were just pet projects for me. I had fun AI slop coding a couple of things, but it was not good software. But if you have a clear and valuable target? AI can absolutely get you there. Multiply that across all your colleagues and a lot /seems/ to be happening, but what is actually moving the needle?
spaceman_2020 5mo ago
I’m also detecting a vibe shift in AI content The mood has gone quickly from “this is cool” to “screw AI and any business that wants to use it” This is particularly clear among the taste making class
- new_account_101 5mo ago
  [dead]
spjt 5mo ago
I wish I could do the same thing. Coworkers would be allowed to ask me X number of questions per month, and once they hit that limit I get the rest of the month off.
- sigmar 5mo ago
  lol. Solid idea. Going to add an email signature with "Emailing me is billed at the following rates: $20k/M token input, $100k/M token output"
alextillman 5mo ago
This is because the current AI approach relies on AI to be a glorified search engine – know everything about everything requiring enormous, ever growing models, and demanding search-engine like near instant responses requiring bigger more complex chips and sprawling data centers to run them in. This leads to a loop demanding ever bigger models, updated at a more and more expensive cost, and chipsets that become much more expensive to deploy. If you move those things to software and utilize tools that are cheap at scale (databases, web search etc.) the hardware arms race ends and the price becomes sustainable. With the right tools preparing dynamic context for a conversation, models are used for their reasoning and not for their knowledge. And waiting even a minute or two for a model to prepare a response, evaluate it, and iterate to improve quality makes a huge difference.
1vuio0pswjnm7 5mo ago
"“It’s a real dollar investment,” says Tan, speaking for Claudeholics who go full blast. “You actually have to spend six to seven figures on tokens—I’m on a run rate to do seven figures this year.”" https://www.wired.com/story/how-ai-agents-plunged-tech-world-into-chaos/ https://www.wired.com/story/how-ai-agents-plunged-tech-world...
- 4hsgf 5mo ago
  Has Wired gone evil now too? Just because some SV programmer circles who excel at marketing switched from Ayahuasca to a new drug does not mean everyone is going to use the new drug. There are literally no good programmers mentioned in that article. They are all boiler room VC types. Shame on Levy, this article is planted or has has no clue.
- 1vuio0pswjnm7 5mo ago
  Was -1
  - 1vuio0pswjnm7 5mo ago
    -1,0,1,2
stego-tech 5mo ago
The AI fever pitch has done a great job at exposing which companies were run with a degree of sanity, versus who bought blindly into the hype train narrative of worker replacement and went all-in. Look, LLMs thrive when they’re given structured data that’s well annotated, clear direction, and treated as the probabilistic machines they are. Not one of those meshes with the AI narrative of “works on existing stuff, requires minimal guidance, and can behave deterministically.” I said as much in 2024 when my employer at the time was grading folks on AI usage while my role was entirely deterministic in nature. It didn’t resonate with specific leadership then, it doesn’t seem to be doing so in the larger market now, and unfortunately not one of these dolts will suffer any consequences for their organizational myopia.
- andai 5mo ago
  Maybe management is a more reasonable target for human equivalence ;)
  - stego-tech 5mo ago
    I mean most managers in my incredibly subjective experience are indistinguishable from the probability slot machines that are LLMs, and those who weren’t were often managers I’d walk through fire for. I’d love to see more research on the efficacy of LLMs as organizational middle management, but I fret that without sufficient anonymity protections for staff they’ll just do the same biased shit humans do.
andai 5mo ago
These two paragraphs were paywalled for me. https://archive.ph/crTG8 https://archive.ph/crTG8 If I understood correctly, a few months ago Anthropic and OpenAI both started charging per-token billing at API pricing for Enterprise customers? i.e. representing roughly a 10x price increase? That's kinda nuts. Similar discussion yesterday: https://news.ycombinator.com/item?id=48296794 https://news.ycombinator.com/item?id=48296794
deleted 5mo ago
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murphomatic 5mo ago
The classic blunder of believing that there is, in fact, a "free" lunch.
Finnucane 5mo ago
"Most people default to automating tasks they dislike rather than tasks most valuable to the company," Well, no shit, but also: suggests those tasks have questionable value? And also: this is why I learned to write code in the first place.
superloika 5mo ago
> "Most people default to automating tasks they dislike rather than tasks most valuable to the company," Sophia Velastegui, CEO of Velastegui Ventures and former chief AI officer at Microsoft, told Axios. Instead, they should focus on using AI to drive revenue. That's right! Work, slave, pain away every day! How dare you make your life a bit less miserable?!
IgorPartola 5mo ago
> Corporate leaders are starting to question whether soaring AI spending is delivering meaningful returns. This is act one the AI bear market. Yes I know everyone screams “bubble”. Let me explain the scenario I have in mind. 1. AI booms because the technology seems to actually have promise of revolutionizing how work gets done. It can do your taxes! It can drive Excel! It can act as a CEO! It can code up full apps and SaaS products! It can replace this vendor or that! You know the drill. 2. Every company must in corporate AI or be seen as obsolete. Having a bad quarter? Announce that you are “seeking to explore opportunities to develop an AI integration plan framework” for your plumbing business. Massive AI compute buying happens. While two of the three major AI houses are not publicly traded proxies like Nvidia and RAM manufacturers are so the market rips higher and higher. Nvidia trades as if it is already 10+ years from now, every company out there has adopted AI perfectly, and it is delivering huge profits to them. 3. Reality checks start pouring in. Turns out that not only is AI expensive (a problem that presumably will be taken care of with time and development), but that the technology itself just isn’t suitable for everything. (IMHO it’s great at augmenting a power user but it is terrible at interacting directly with customers). We start seeing individual companies change tone on investment. They can’t stop it due to momentum but they are starting to shift the narrative to warn of what comes next. This is where we are. 4. Numbers come in. Earnings show what the actual ROI is. Some companies do benefit, but crucially we see examples of where investing in AI destroys value. I think this happens when replace crucial parts of their workforce with agents and find that they lost in-house expertise, when customers left due to worse products, or simply when AI was roughly as expensive as human labor without being significantly more productive. 5. The market stumbles. What do you mean AI won’t take over every corporate America?! Surely that can’t be right! Nvidia and other proxies flag. 6. In a late to the game rush Anthropic and OpenAI IPO fearing that the market has noticed that the emperor has no clothes. Their internal numbers turn out to be scary: very high revenue but no path to insane profitability. They quickly get included in QQQ and maybe even S&P500 but as their IPO price is the highest they trade they drag the broad market indexes down. This is leveraged by the Nvidia proxy status. 7. Infrastructure course correction. Hyperscalers who started huge datacenter buildouts cannot justify it. They pay contract penalties and get out of some of the projects, writing down losses. The market fully melts. —- I think there is a competing market downturn fueled by the affordability squeeze. Basically while AI spend is corporate driven, the biggest investors are consumer companies. Of the hyperscalers you can maybe argue that Microsoft is not a B2C fully but it is close. If consumers don’t have money to spend, hyperscalers take a hit, investment slows from there, and AI is hit directly by it. I think either scenario is likely, it’s just which happens first. But right now the market is sprinting down a tight rope and trading like that tight rope has no end and that the sprinter never makes a mistake regardless of wind changes. Everything has to go right for a very long time to justify valuations. One stumble can stop it all.
woeirua 5mo ago
There's a very real possibility that we end up with a bunch of companies simultaneously realizing that they just don't have any good ideas to leverage AI on and rushing more code out the door doesn't lead to tangible value. Many execs are going to realize that they're no longer growth companies and that paying $500k a year for engineers no longer makes sense... If that's the case, then I do expect the AI bubble is going to pop spectacularly next year as token budgets are going to collapse. The damage to the tech industry is going to be catastrophic. If you think the job market is bad now, wait until data center spending goes off a cliff.
rolfen 5mo ago
Corporation always keep doing this, they hire lousy programmers then they try to make them produce good code by forcing them to use all kinds of hyped cutting edge technologies. I'm sure there is an explanation for why they keep doing it.
ChrisArchitect 5mo ago
This is just links to stories that are already being discussed in other threads here OP. https://news.ycombinator.com/item?id=48268871 https://news.ycombinator.com/item?id=48268871 https://news.ycombinator.com/item?id=48238896 https://news.ycombinator.com/item?id=48238896 https://news.ycombinator.com/item?id=48021368 https://news.ycombinator.com/item?id=48021368 https://news.ycombinator.com/item?id=48173318 https://news.ycombinator.com/item?id=48173318
phyzix5761 5mo ago
We're at the point now with AI where people are realizing that innovation doesn't happen automatically when you have more resources or the ability to crank out more output. Innovation usually requires real problems to solve, a limitation on resources, and creative people working on problems they find interesting. If you're in a mature industry, chances are, there is little room to innovate with AI. Not because AI isn't a wonderful tool but because your company, and competitors, have put in hundreds of thousands of human hours into solving the problems of your industry. If they haven't come up something innovative in the last 5 to 10 years, AI probably isn't either. The speed of writing code was never the bottleneck in software. Yes, AI can do it faster, but the parts that are most challenging are finding a market and figuring out how to best serve it. Those are the parts that take the longest and, often, the most resources. In reality, this is the real business of any company, what they produce is just a side effect of finding these two things. AI hasn't shown much promise in this regard. There are some simulated and small real world tries like what Andonlabs[1] is doing but it seems humans are still better at this kind of problem solving. Companies have been spending ridiculous amounts of money trying to squeeze innovation out of a tool that is designed to produce statistically average results. This leads to mass layoffs because workers, who also produce average results, are seen as redundant. But when average workers come together they can produce extraordinary results through the mere act of working on something long enough and synthesizing ideas. Eventually, someone will say or write something that triggers a thought for someone else and it leads to a breakthrough. AI can't do this, yet. [1] https://andonlabs.com/blog/andon-market-launch https://andonlabs.com/blog/andon-market-launch
eggplantemoji69 5mo ago
I’ve said from the beginning that these tools may be helpful but on average will not replace humans and be as revolutionary as how they’re being touted. However, given government budget deficits and the need to outgrow inflation / the ever increasing annual interest burden the US gov carries, AI kinda HAS to be an insane productivity booster or else everything is kinda effed. As I understand it, most of us economy / sp 500 growth in the last year or two has been attributed to AI spend and speculation…
senectus1 5mo ago
Sat through a demo of a tool that now has AI shoehorned into it yesterday. At one point i noticed that the demo had a column that showed how many tokens each AI query was using.. one used 250 THOUSAND (for a single analysis of a single device). I asked the company who is footing the bill for those tokens.. they say they are (*for now). I pointed out the rather high number of tokens being used and does that mean we get a budget or quota or is it all you can eat. they said it was a good question and they'd have to find out... and then one of the execs said OUT LOUD "Why is that column even there? Why do we show this to the customers" I lol'd. It wasn't taken very well.
xh638 5mo ago
[flagged]

172 points by 1vuio0pswjnm7 5mo ago

> Instead, they should focus on using AI to drive revenue. There is a complete disconnect between wages of employees and company's revenue => Why aren't employees working towards revenue? What a mystery. Children, let's help Elmo solve this mystery. And then random mass layoffs to make numbers for shareholders look great in quarterly reports. Surely this motivates people work to their fullest potential and to care for company's revenue.

roxolotl 5mo ago
Even better there’s a complete disconnect between revenues and metrics we use to measure productivity. Corporate wants to believe there’s numbers you can use to measure knowledge workers like widget makers where there’s really not much that’s effective beyond revenue.
mapontosevenths 5mo ago
I found this claim interesting so I looked into it. Everything I can find shows that the intuition is accurate. Companies with EOSP programs outperform those that do not in the market by about 17%.[0] Companies that perform layoffs, despite short-term stock boosts, underperform on a period of years showing a 14% decline in their Return on Assets (ROA) in the years following the layoffs.[1] [0] https://www.nceo.org/employee-ownership-blog/new-study-shows-esop-company-stock-prices-outperformed-market-indices https://www.nceo.org/employee-ownership-blog/new-study-shows... [1] https://www.researchgate.net/publication/277473996_Financial_consequences_of_employment-change_decisions_in_major_US_corporations https://www.researchgate.net/publication/277473996_Financial...

Spide_r 5mo ago

https://archive.is/crTG8 https://archive.is/crTG8

CuriouslyC 5mo ago

This is almost entirely on Anthropic and the stupid C suite people trying to push TokenMaxxing. GPT5.5 is much more token efficient, other models are much cheaper, and if used in moderation rather than than trying to get everyone to OpenClaw 24/7 with token leaderboards, it's much more economical. Also ironically, a lot of GenZ and young Millenials who were already bitter at their employers have used the tokenmaxxing push to sabotage the AI rollouts by burning tokens on stupid shit. It seems to be working.

kleiba2 5mo ago
Citation needed.
throwatdem12311 5mo ago
I’m an “old millenial” and the excessive burning of tokens will continue until working conditions improve.
- voidfunc 5mo ago
  Working conditions are fine, I simply am not incentivized to be efficient with tokens.
  - throwatdem12311 5mo ago
    Yeah, everything is fine until you don’t want to use AI for something because it sucks at that task and then you end up on a PiP because your token burn is low. Why the f*ck are AI Token Use Leaderboards even a thing. Features that used to take months are now expected in days. Oh you didn’t merge 40 pull requests and deploy to prod 15 times today? Aren’t you using Opus the greatest thing since the invention of the wheel?! What do you mean it’s hard to review 100 merge requests per day? Just have Claude review it! That’s a PiP. Oh prod is down because people keep deploying code that nobody even freakin’ read? Just have Claude fix it! What do you mean it’s doesn’t work well? Just burn more tokens or you’re on a PiP. Surely there wouldn’t be malicious compliance by people that would prefer to use the right tool for the job instead of having this crap shoved down our throats by management by threat of termination.

Arodex 5mo ago

>Corporate leaders are starting to question whether soaring AI spending is delivering meaningful returns. We should start to question whether soaring CEO salary spending is delivering meaningful results.

utopiah 5mo ago
Ah, that's not how it works : CEOs are rich so they are successful. They are successful so they are rich. Q.E.D.
- hatefulheart 5mo ago
  Maybe in your fantasy world. In reality people are rarely rich based on merit alone. EDIT: Sorry it was a really clever joke.
  - spacechild1 5mo ago
    I think you missed the joke.
  - yulker 5mo ago
    It's sarcasm, obviously.
  - asdfasvea 5mo ago
    >>>EDIT: Sorry it was a really clever joke. I sincerely hope that was your attempt at sarcasm.
    - raffael_de 5mo ago
      exactly my thought.
- aleph_minus_one 5mo ago
  > CEOs are rich so they are successful. "Successful" in which sense? The most reasonable definition "Successful in convincing other people to give them money" is rather a tautology. :-) A very related problem concerning your argument is well-known for decades: the Principal–agent problem: > https://en.wikipedia.org/wiki/Principal%E2%80%93agent_problem https://en.wikipedia.org/wiki/Principal%E2%80%93agent_proble... It says that the self-interest of an agent (e.g. the CEO) is not identical to the interests of the principal (e.g. the shareholders). Why do I mention this? The CEO being rich is a measurement of the financial success of the agent, but not of the principal. You are rather interested in measuring the success of the principal.

Arodex 5mo ago

Just a week ago, Anthropic barely breaking even was hailed as AI companies being close to profitability much earlier than forecast. In fact it is all smoke and mirrors, pure mania from C-level executives out of their depth trying to one-up each other with company money, and they aren't even close.

mrweasel 5mo ago
I didn't look into the numbers myself, but Ed Zitron claimed in his podcast that the only reason Anthropic looks sort of profitable was due to some rather clever accounting (not illegal) and a spending that didn't happen, I think. Things haven't actually improved much, but if you zoom into a very selective part of the fiscal year it looks promissing. https://www.iheart.com/podcast/1119-better-offline-150284547/episode/monologue-anthropic-is-not-profitable-unless-334441675/ https://www.iheart.com/podcast/1119-better-offline-150284547...
croes 5mo ago
They become profitable but on the expense of fools like that company.

cmiles8 5mo ago

Playing out in company after company right now: CEOs: “Get me some of that GenAI” CTO: “OK, we have all the GenAI” CEOs: “Employees, it’s AI or bust” Employees: Tokenmax CFO: “Um, this is costing a ton and we’re not seeing savings or efficiency materialize.” CEO: “Are we getting any value out of this?” COO: “Not really, and frankly I’m getting annoyed at all the AI slop turning up all over.” CEO: “OK, well, let’s do a big layoff and then I’ll just say it was because of AI. Hopefully folks won’t blame me for the mess and I’ll just talk about how amazing AI is.”

utopiah 5mo ago
> Hopefully folks won’t blame me for the mess Lesson #1 from business school : take all credits, put the blame on others, if there no easy scapegoat blame the "economical context" Lesson #2 and beyond : just see lesson #1, it's enough. You've made it and it's ALL thanks to this amazing business school degree you got, now go profits with your new already wealthy peers.
- randusername 5mo ago
  I have a literal ledger tracking the number of times executives have used the phrase "evolving capital markets" It's amazing to me how subtle the difference can be between a business leader that seems to know what they're doing and one that clearly does not. Same words, even, but from one mouth it's compressing a complex thought and from another it's word salad to give the appearance of complex thought.
  - utopiah 5mo ago
    Regurgitating word salad coming from Harvard Business Review or whatever publication is trendy at the moment. Indeed the "worst" part is that the initial concept might very well make sense, even be grounded in actual research. Masters of semblance.
jillesvangurp 5mo ago
These are golden times for AI consulting. We're getting into that business because it is up for grabs. Everybody as AI FOMO right now and begging people to take their money. Exactly what you are highlighting. And, yet, nobody has the beginning of a clue what to do or how to do stuff with AI. That's classic consulting territory. My analysis of the whole space is that all the tech people are focused on completely the wrong end of the problem space (model quality, training, token cost, etc.). They are geeking out on that stuff. Worse, they are mostly not even that good at using their own tools. I regularly talk to so called "AI native" companies that are hiring enterprise sales people to do sales like it's 2006 instead of 2026. Their product is AI native, but their companies aren't. The real issues are on the low level plumbing end. How do you connect all the data silos you have. Are they even the right silos still? And once you fix that: how do you get organized around tapping into those. What guardrails do you need? How do you deal with compliance issues? Etc. You don't need to do a lot to get value back. Most people haven't gone there yet. Mostly people actually already have and pay for the tools that would enable a lot more if only they knew how: ChatGPT, Codex, Manus, Perlexity Computer, Claude CoWork, etc. What you are outlining is funny but true. The issue isn't money or tools but figuring out what to do with the tools you already bought.

swader999 5mo ago

"An AI consultant tells Axios one of their clients recently spent half a billion dollars in a single month after failing to put usage limits on Claude licenses for employees." Like physically, how could this even happen?

pjc50 5mo ago
Agents. An agent is a system for spinning up processes that use tokens, talking to other processes that use tokens. I wonder how many megawatts that waste represented. Just one guy, worse than a small air force of private jets.
layer8 5mo ago
This could happen with a large number of integrations or agent swarms working 24/7 with high throughput and long contexts.
ludicrousdispla 5mo ago
Maybe the AI consultant gets a cut of that half billion?
spacechild1 5mo ago
Let's not forget about the environmental impacts. It's crazy that people are willfully burning so much energy for almost no return. And we thought bitcoin was bad... This is just completely irresponsible, if not sociopathic behavior.
- slfnflctd 5mo ago
  Bitcoin doesn't have long conversations with you, including deeply technical ones, in a way that you thought only a human being could just 5 years ago. They are not the same. I agree fully with you on the potential for energy waste. We always do that, though, with nearly everything. How many of today's jet plane flights really needed to happen? The question is how much value people feel they're getting. People are having a whole lot more feelings about AI than they ever could about cryptocurrencies, and that train aint stoppin'.

autoexec 5mo ago

Just wait until companies are dependent on on it. When their employees can't think without it. When their AI generated codebase is such a mess they'd need a rewrite to understand it without AI. When they've got AI embedded in all their internal processes and tools. Then massive price hikes will come because they've been bent over a barrel and they'll have no alternative that isn't at least as painful in the short-term as letting the AI company fuck them. The long term won't matter then because any company capable of seeing past the short term wouldn't let themselves get into that position in the first place.

irishcoffee 5mo ago
[dead]

lelanthran 5mo ago

I am Jack's total lack of surprise :-/

dylan604 5mo ago
How much longer before we get to the “I get cancer. I kill Jack” stage? Isn’t uncontrolled growth a sign of cancer? Or is it more virus like where it just continues to grow without ever reaching a balance with its surroundings?
- andai 5mo ago
  >declare war on natural ecosystem >win

Balinares 5mo ago

Overheard recently: "Thanks to AI we're producing more code and more MRs, faster than ever, but the milestones aren't getting hit any sooner. Actually the opposite, if anything." I wonder how widespread that phenomenon is. Perhaps it's no wonder the prominent actors are trying to rush to IPO...

FerretFred 5mo ago
Was that at Microsoft by any chance?
mapontosevenths 5mo ago
Goodharts law. The metrics were always measuring the wrong thing, and now that we've finally optimized for the wrong thing successfully management will be forced to admit it and move on to another, slightly different, metric that doesn't actually equate to shareholder value. It doesn't matter what the line actually measures, just that it goes up.
whobre 5mo ago
That's exactly what's happening. Many claim they are more productive with AI, but individual rise in productivity just doesn't translate to projects being completed any sooner. And by "projects", I mean corporate ones with big teams involved. Hobby projects actually do get finished much faster.
- nijave 5mo ago
  In the corporate world, writing code was always a small chunk anyway. Iirc something like 30% of employee time. Getting 50% faster there still only gains back 10% of your time. To further complicate matters, you had to spend on AI software and potentially additional on legal/risk/security/compliance to enable that. The smaller the company, the bigger that % of coding is of total time (all the way down to hobby where the majority of time is spent coding)
  - ryandrake 5mo ago
    Where I work, I would guess that, out of the amount of person-hours spent on a project, less than 5% of it is the cumulative time spent designing and writing code. There's so much other stuff going on: Requirements gathering, "aligning" with other teams, human reviews, QA, presenting to executives, waiting for approval from executives, reporting status, deploying to staging, internal dogfooding, slow ramp-ups to production... This is how projects that are 50 lines of code take 3 months to deploy. AI is helping reduce the time spent on that 2%.

mystraline 5mo ago

Well, if AI has a massive sticker shock attributed, so we should target the high value roles and should save money, right? So im looking at CEO, CTO, CFO, and all the chief-something-officer. If LLMs are that totally amazing at thinking, then we should be targeting upper management, not the workers. That would save a LOT of money for the shareholders! /snark We all know why they wont.

59percentmore 5mo ago
So it goes. Wage theft dwarfs the amount lost to street-level theft, robbery, burglary, etc., combined. The economic stimulus from correcting even a portion of annual wage theft would represent complete coverage of those violent thefts - economically-speaking, there would be no reason for criminals to carry them out. Why rob a gas station to get your drug money? Everyone around you is making enough extra at work that bumming a dollar here and there covers it. That sort of thing. But good forbid we actually correct a major social ill at the expense of the people who profit from it.
- mystraline 5mo ago
  Exactly. And even worse is that crime itself is firmly rooted in politics. Example: You work at walmart, as a cashier. You drop a $100 bill on the floor and pocket it from the till. You're caught, cops called, and you are arrested. Example: You work as a manager at the same walmart. Store manager says labor costs are too damned high. So you go in on 10 employees, and edit their timecards to cut $100 from each of them, totaling $1000. IF you are caught, police will not respond. Instead, it is a "civil matter". This is a bit dated chart, but its still very much correct. https://www.tcworkerscenter.org/2018/09/wage-theft-vs-other-forms-of-theft-in-the-u-s/ https://www.tcworkerscenter.org/2018/09/wage-theft-vs-other-... But notice the wage theft types are all "civil matters", and the non-eage theft are heavily criminally prosecuted. And who does those? Predominantly poorer people. We also see this with dumping trash, being criminal and severe to the individual, but companies (read: Musk) can dump thousands of gallons of toxic sludge per day. https://www.yahoo.com/news/articles/inspection-texas-drainage-ditch-reveals-170629588.html https://www.yahoo.com/news/articles/inspection-texas-drainag... We also see criminality differences between charges of freebase cocaine versus crack cocaine. Crack was what black people smoked, so sentencing was like 10x of freebase. When you start looking at how laws are apllied, its almost always the same pattern: those at the top are a civil matter. Those who report to the top are a criminal matter. Those at the bottom are "charged with the fullest maximum punishment".

ecshafer 5mo ago

>Corporate leaders are starting to question whether soaring AI spending is delivering meaningful returns. This isn't surprising. Ive recently run into quite a few rabbit holes where AI is bad enough that its much more efficient to do it myself. I wanted to refactor some code, gave it a design pattern to go towards, some specific classes and methods, etc. making it a well described problem. AI just couldn't do it satisfactorily. The code was ugly, overly verbose, and after multiple tries with multiple prompts saying to keep things simple. They still would introduce new classes, useless fields, etc.

chrisweekly 5mo ago
"AI" is "bad" and "just couldn't do it"? Specifics w model and harness would lend more credence.
- ecshafer 5mo ago
  This was GPT 5.5 and codex. The specific model and harness isn't that important here. AI could do it. But the issue seems to be that there are some tasks where AI kind of falls over and provides poor results. It was easier, better, and faster for me to just do it myself. I have found a lot of cases where AI is great. If you have a UML diagram already, or translating code from language x to y, fixing unit test failures, generating boiler plate. But I can definitely see if people are using large amounts of AI for writing code, analyzing code, etc. that they are not actually seeing returns.
new_account_101 5mo ago
[dead]

imglorp 5mo ago

This is an important inflection point. When tokens get correctly priced, all of the insane over-investment in capital will need to draw back: buying data centers, semiconductors, and politicians. Even then, it won't be right-priced with regard to actual costs. The environmental impact should have been priced in from the beginning. There seems to be a parallel with subsidizing fossil fuels, under pricing them which encourages over dependence, ignoring the real costs society will pay later.

whazor 5mo ago
It rather looks like chatgpt/antrophic enterprise tokens and API calls are too expensive. Competition is quite strong on openrouter. However, the real problem is running wild with token burning. With parallel agents calling subagents you can burn lots of tokens per minute. Especially with thousands of engineers.
somenameforme 5mo ago
I've yet to see any compelling data about inference being particularly expensive. For local LLM models, that are becoming increasingly viable, it's dirt cheap. The same is also true in image gen world where now even a heavily dated GPU can cheaply and quickly produce high quality images. I also think the image gen world is a useful analog because there are a million sites, presumably still making money, with markups that are multiple orders of magnitude off their costs. They're feeding off user ignorance that was, at least in part, artificially seeded by implying high costs for image gen back in its day. Though it's possible/probable that the initial training runs were expensive, but that's a one-and-done cost.

internet_points 5mo ago

https://www.merriam-webster.com/dictionary/sticker%20shock https://www.merriam-webster.com/dictionary/sticker%20shock oh. i thought it was about people putting up stickers like https://mastodon.social/@spellingmistakescostlives@mastodon.ie/116611777282440254 https://mastodon.social/@spellingmistakescostlives@mastodon....

stockresearcher 5mo ago

We use GH Copilot at work and this week sat for a presentation by GH about optimizing token usage and maximizing ROI on tokens used. Anyone else get this presentation? They didn’t have time for questions because they had to run and give it to the next big enterprise on their list… They basically said that everything is too expensive, you have to watch it like a hawk. It was as if they poured a bucket of cold water on the room. People were wondering how they could do anything faster with all these strategies. And then “sorry no questions. Bye!”

karmakurtisaani 5mo ago
We did not have any presentation yet, but the first serious discussion about the cost of tokens has started on the documentation level. Looking forward to seeing these presentations!
Esophagus4 5mo ago
Did you have any good tips for optimizing usage? The ones I’ve stumbled upon seem to be: switch models based on task complexity, use tooling like ASTs and compression, disable unused MCPs, compact often, be verbose with input to give clear guidance…
- deadeye 5mo ago
  I don't think compacting often is good for saving money. It generates more output tokens and then the input is no longer from cache, which is priced differently...typically very differently.
spaceman_2020 5mo ago
Just hire people and pay then a fair wage and let everyone get richer together ffs When did American capitalism become such a zero sum game
- rickydroll 5mo ago
  When the powers that be decided labor didn't matter and the only thing that mattered was capital. One will never get rich on wages. The only way to get rich is through asset manipulation and rent-seeking.

deleted 5mo ago

[deleted]

TSiege 5mo ago

I really can't tell what is going on with AI these days. I hear AI labs claiming theyre profitable or close to it. I hear companies say they're dubious the juice is worth the squeeze. I've seen anecdotal claims of a measurable increase in productivity of 2x in PRs created and merged coming in at cost 20% of engineering employee budget. Others say they're still getting no value (which I doubt). Simon Willison's recent post went into debunking the AI sticker shock claims somewhat. Either way this seesawing between new golden era and the greatest VC money furnace is becoming exhausting. I'd like to see real numbers at this point, and this article is just a few bullet points that link to other articles. Talk is far cheaper than tokens and I'd like to have a workflow that I can rely on being there in six months. https://simonwillison.net/2026/May/27/product-market-fit/#the-ai-failure-stories-around-this-are-pretty-thin https://simonwillison.net/2026/May/27/product-market-fit/#th...

bitexploder 5mo ago
AI Has empowered people to build things much more quickly. Not slop if you are even a little conscientious about how you use it. What it does not do fix the human structural problems. If you are solving the wrong problems you aren’t doing anything useful. Just because you can now take an idea to near completion doesn’t mean it was worth doing, but now you spent tokens and a lot of your mental bandwidth to finish it. Or worse you let it become slop and it will fall apart if you even look at it funny. Previously if I needed to automate something I thought really carefully about it. Now, I still think really carefully about it. I had fun AI coding some tools I always wanted but they were just pet projects for me. I had fun AI slop coding a couple of things, but it was not good software. But if you have a clear and valuable target? AI can absolutely get you there. Multiply that across all your colleagues and a lot /seems/ to be happening, but what is actually moving the needle?

spaceman_2020 5mo ago

I’m also detecting a vibe shift in AI content The mood has gone quickly from “this is cool” to “screw AI and any business that wants to use it” This is particularly clear among the taste making class

new_account_101 5mo ago
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spjt 5mo ago

I wish I could do the same thing. Coworkers would be allowed to ask me X number of questions per month, and once they hit that limit I get the rest of the month off.

sigmar 5mo ago
lol. Solid idea. Going to add an email signature with "Emailing me is billed at the following rates: $20k/M token input, $100k/M token output"

alextillman 5mo ago

This is because the current AI approach relies on AI to be a glorified search engine – know everything about everything requiring enormous, ever growing models, and demanding search-engine like near instant responses requiring bigger more complex chips and sprawling data centers to run them in. This leads to a loop demanding ever bigger models, updated at a more and more expensive cost, and chipsets that become much more expensive to deploy. If you move those things to software and utilize tools that are cheap at scale (databases, web search etc.) the hardware arms race ends and the price becomes sustainable. With the right tools preparing dynamic context for a conversation, models are used for their reasoning and not for their knowledge. And waiting even a minute or two for a model to prepare a response, evaluate it, and iterate to improve quality makes a huge difference.

1vuio0pswjnm7 5mo ago

"“It’s a real dollar investment,” says Tan, speaking for Claudeholics who go full blast. “You actually have to spend six to seven figures on tokens—I’m on a run rate to do seven figures this year.”" https://www.wired.com/story/how-ai-agents-plunged-tech-world-into-chaos/ https://www.wired.com/story/how-ai-agents-plunged-tech-world...

4hsgf 5mo ago
Has Wired gone evil now too? Just because some SV programmer circles who excel at marketing switched from Ayahuasca to a new drug does not mean everyone is going to use the new drug. There are literally no good programmers mentioned in that article. They are all boiler room VC types. Shame on Levy, this article is planted or has has no clue.
1vuio0pswjnm7 5mo ago
Was -1
- 1vuio0pswjnm7 5mo ago
  -1,0,1,2

stego-tech 5mo ago

The AI fever pitch has done a great job at exposing which companies were run with a degree of sanity, versus who bought blindly into the hype train narrative of worker replacement and went all-in. Look, LLMs thrive when they’re given structured data that’s well annotated, clear direction, and treated as the probabilistic machines they are. Not one of those meshes with the AI narrative of “works on existing stuff, requires minimal guidance, and can behave deterministically.” I said as much in 2024 when my employer at the time was grading folks on AI usage while my role was entirely deterministic in nature. It didn’t resonate with specific leadership then, it doesn’t seem to be doing so in the larger market now, and unfortunately not one of these dolts will suffer any consequences for their organizational myopia.

andai 5mo ago
Maybe management is a more reasonable target for human equivalence ;)
- stego-tech 5mo ago
  I mean most managers in my incredibly subjective experience are indistinguishable from the probability slot machines that are LLMs, and those who weren’t were often managers I’d walk through fire for. I’d love to see more research on the efficacy of LLMs as organizational middle management, but I fret that without sufficient anonymity protections for staff they’ll just do the same biased shit humans do.

andai 5mo ago

These two paragraphs were paywalled for me. https://archive.ph/crTG8 https://archive.ph/crTG8 If I understood correctly, a few months ago Anthropic and OpenAI both started charging per-token billing at API pricing for Enterprise customers? i.e. representing roughly a 10x price increase? That's kinda nuts. Similar discussion yesterday: https://news.ycombinator.com/item?id=48296794 https://news.ycombinator.com/item?id=48296794

deleted 5mo ago

[deleted]

murphomatic 5mo ago

The classic blunder of believing that there is, in fact, a "free" lunch.

Finnucane 5mo ago

"Most people default to automating tasks they dislike rather than tasks most valuable to the company," Well, no shit, but also: suggests those tasks have questionable value? And also: this is why I learned to write code in the first place.

superloika 5mo ago

> "Most people default to automating tasks they dislike rather than tasks most valuable to the company," Sophia Velastegui, CEO of Velastegui Ventures and former chief AI officer at Microsoft, told Axios. Instead, they should focus on using AI to drive revenue. That's right! Work, slave, pain away every day! How dare you make your life a bit less miserable?!

IgorPartola 5mo ago

> Corporate leaders are starting to question whether soaring AI spending is delivering meaningful returns. This is act one the AI bear market. Yes I know everyone screams “bubble”. Let me explain the scenario I have in mind. 1. AI booms because the technology seems to actually have promise of revolutionizing how work gets done. It can do your taxes! It can drive Excel! It can act as a CEO! It can code up full apps and SaaS products! It can replace this vendor or that! You know the drill. 2. Every company must in corporate AI or be seen as obsolete. Having a bad quarter? Announce that you are “seeking to explore opportunities to develop an AI integration plan framework” for your plumbing business. Massive AI compute buying happens. While two of the three major AI houses are not publicly traded proxies like Nvidia and RAM manufacturers are so the market rips higher and higher. Nvidia trades as if it is already 10+ years from now, every company out there has adopted AI perfectly, and it is delivering huge profits to them. 3. Reality checks start pouring in. Turns out that not only is AI expensive (a problem that presumably will be taken care of with time and development), but that the technology itself just isn’t suitable for everything. (IMHO it’s great at augmenting a power user but it is terrible at interacting directly with customers). We start seeing individual companies change tone on investment. They can’t stop it due to momentum but they are starting to shift the narrative to warn of what comes next. This is where we are. 4. Numbers come in. Earnings show what the actual ROI is. Some companies do benefit, but crucially we see examples of where investing in AI destroys value. I think this happens when replace crucial parts of their workforce with agents and find that they lost in-house expertise, when customers left due to worse products, or simply when AI was roughly as expensive as human labor without being significantly more productive. 5. The market stumbles. What do you mean AI won’t take over every corporate America?! Surely that can’t be right! Nvidia and other proxies flag. 6. In a late to the game rush Anthropic and OpenAI IPO fearing that the market has noticed that the emperor has no clothes. Their internal numbers turn out to be scary: very high revenue but no path to insane profitability. They quickly get included in QQQ and maybe even S&P500 but as their IPO price is the highest they trade they drag the broad market indexes down. This is leveraged by the Nvidia proxy status. 7. Infrastructure course correction. Hyperscalers who started huge datacenter buildouts cannot justify it. They pay contract penalties and get out of some of the projects, writing down losses. The market fully melts. —- I think there is a competing market downturn fueled by the affordability squeeze. Basically while AI spend is corporate driven, the biggest investors are consumer companies. Of the hyperscalers you can maybe argue that Microsoft is not a B2C fully but it is close. If consumers don’t have money to spend, hyperscalers take a hit, investment slows from there, and AI is hit directly by it. I think either scenario is likely, it’s just which happens first. But right now the market is sprinting down a tight rope and trading like that tight rope has no end and that the sprinter never makes a mistake regardless of wind changes. Everything has to go right for a very long time to justify valuations. One stumble can stop it all.

woeirua 5mo ago

There's a very real possibility that we end up with a bunch of companies simultaneously realizing that they just don't have any good ideas to leverage AI on and rushing more code out the door doesn't lead to tangible value. Many execs are going to realize that they're no longer growth companies and that paying $500k a year for engineers no longer makes sense... If that's the case, then I do expect the AI bubble is going to pop spectacularly next year as token budgets are going to collapse. The damage to the tech industry is going to be catastrophic. If you think the job market is bad now, wait until data center spending goes off a cliff.

rolfen 5mo ago

Corporation always keep doing this, they hire lousy programmers then they try to make them produce good code by forcing them to use all kinds of hyped cutting edge technologies. I'm sure there is an explanation for why they keep doing it.

ChrisArchitect 5mo ago

This is just links to stories that are already being discussed in other threads here OP. https://news.ycombinator.com/item?id=48268871 https://news.ycombinator.com/item?id=48268871 https://news.ycombinator.com/item?id=48238896 https://news.ycombinator.com/item?id=48238896 https://news.ycombinator.com/item?id=48021368 https://news.ycombinator.com/item?id=48021368 https://news.ycombinator.com/item?id=48173318 https://news.ycombinator.com/item?id=48173318

phyzix5761 5mo ago

We're at the point now with AI where people are realizing that innovation doesn't happen automatically when you have more resources or the ability to crank out more output. Innovation usually requires real problems to solve, a limitation on resources, and creative people working on problems they find interesting. If you're in a mature industry, chances are, there is little room to innovate with AI. Not because AI isn't a wonderful tool but because your company, and competitors, have put in hundreds of thousands of human hours into solving the problems of your industry. If they haven't come up something innovative in the last 5 to 10 years, AI probably isn't either. The speed of writing code was never the bottleneck in software. Yes, AI can do it faster, but the parts that are most challenging are finding a market and figuring out how to best serve it. Those are the parts that take the longest and, often, the most resources. In reality, this is the real business of any company, what they produce is just a side effect of finding these two things. AI hasn't shown much promise in this regard. There are some simulated and small real world tries like what Andonlabs[1] is doing but it seems humans are still better at this kind of problem solving. Companies have been spending ridiculous amounts of money trying to squeeze innovation out of a tool that is designed to produce statistically average results. This leads to mass layoffs because workers, who also produce average results, are seen as redundant. But when average workers come together they can produce extraordinary results through the mere act of working on something long enough and synthesizing ideas. Eventually, someone will say or write something that triggers a thought for someone else and it leads to a breakthrough. AI can't do this, yet. [1] https://andonlabs.com/blog/andon-market-launch https://andonlabs.com/blog/andon-market-launch

eggplantemoji69 5mo ago

I’ve said from the beginning that these tools may be helpful but on average will not replace humans and be as revolutionary as how they’re being touted. However, given government budget deficits and the need to outgrow inflation / the ever increasing annual interest burden the US gov carries, AI kinda HAS to be an insane productivity booster or else everything is kinda effed. As I understand it, most of us economy / sp 500 growth in the last year or two has been attributed to AI spend and speculation…

senectus1 5mo ago

Sat through a demo of a tool that now has AI shoehorned into it yesterday. At one point i noticed that the demo had a column that showed how many tokens each AI query was using.. one used 250 THOUSAND (for a single analysis of a single device). I asked the company who is footing the bill for those tokens.. they say they are (*for now). I pointed out the rather high number of tokens being used and does that mean we get a budget or quota or is it all you can eat. they said it was a good question and they'd have to find out... and then one of the execs said OUT LOUD "Why is that column even there? Why do we show this to the customers" I lol'd. It wasn't taken very well.

xh638 5mo ago

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