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Hacker News Hacker NewsWe should start to question whether soaring CEO salary spending is delivering meaningful results.
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.
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.
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!”
I wonder how widespread that phenomenon is. Perhaps it's no wonder the prominent actors are trying to rush to IPO...
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.
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.
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.
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/#th...
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.
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.
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…
I'm sure there is an explanation for why they keep doing it.
That's right! Work, slave, pain away every day! How dare you make your life a bit less miserable?!
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
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.
https://www.wired.com/story/how-ai-agents-plunged-tech-world...
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.
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.
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:
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.
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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.
https://news.ycombinator.com/item?id=48268871
https://news.ycombinator.com/item?id=48238896
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.
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.”
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.