I think Anthropic and OpenAI have found product-market fit • Hacker News Board

Re: I think Anthropic and OpenAI have found product-market fit

#241

Post by remus » Wed, May 27, 2026, 7:03 PM UTC

eqvinox wrote: post #86

simonw wrote: post #16

Earlier quoted context omitted.

I'm not sure what you're pushing back against here. I spent $200. If I had been paying API pricing it would have been $2,180.16. The article is about how enterprise customers get charged API pricing, which means if I had been employed by one of those companies I would have cost them $2,180.16. What am I missing?

Just because API pricing would've been $2180.16 doesn't mean that's the value of those tokens. For starters, you personally probably wouldn't have paid that. But also, sales price isn't value. This is like saying, oh, I saw this bar of gold somewhere for $10000 but got it here for $1000! So I got $10000 worth of gold for $1000! - no, the value of that gold is determined by its weight, which wasn't even mentioned. We…

> Just because API pricing would've been $2180.16 doesn't mean that's the value of those tokens.

You seem to be suggesting the price of tokens is entirely disconnected to the cost of providing the service? I don't see much basis for that assumption.

Re: I think Anthropic and OpenAI have found product-market fit

#242

Post by aspenmartin » Wed, May 27, 2026, 7:04 PM UTC

eqvinox wrote: post #86

simonw wrote: post #16

Earlier quoted context omitted.

I'm not sure what you're pushing back against here. I spent $200. If I had been paying API pricing it would have been $2,180.16. The article is about how enterprise customers get charged API pricing, which means if I had been employed by one of those companies I would have cost them $2,180.16. What am I missing?

Just because API pricing would've been $2180.16 doesn't mean that's the value of those tokens. For starters, you personally probably wouldn't have paid that. But also, sales price isn't value. This is like saying, oh, I saw this bar of gold somewhere for $10000 but got it here for $1000! So I got $10000 worth of gold for $1000! - no, the value of that gold is determined by its weight, which wasn't even mentioned. We…

He's saying he's getting a great deal...a token from Opus on Claude code is the same as a token from Opus on the API. I remain as confused as Simon. He's not talking about "here's the ROI I got from my $100 subscription" it's "here's how much I saved from getting the monthly subscription instead of sending things through an API".

Re: I think Anthropic and OpenAI have found product-market fit

#243

Post by hansmayer » Wed, May 27, 2026, 7:05 PM UTC

pier25 wrote: post #185

hansmayer wrote: post #128

> Anthropic are strongly rumored to be about to have their first profitable quarter No, its more like their own leak to WSJ and according to Ed Zitron -> seems to be heavily engineered via non-GAAP practices such as counting potential , but not realised revenue as actual revenue - the stuff for which I would be arrested if I did it at my company. Also it appears according to Ed's analysis - strangely they seem to be…

Yeah I'll believe it when I see it. Revenue is increasing but so are their costs. Back in 2024 their CEO claimed training costs would rise to $10-100B in the next years. https://www.tomshardware.com/tech-industry/artificial-intell...

Their CEO claims a lot of wild shit. He claimed in January this year, that in about 2-3 weeks from this moment, i.e. "in 6 months" that AI will be doing all of SWE work. Lets hold these people accountable for a change!

Re: I think Anthropic and OpenAI have found product-market fit

#244

Post by simonw » Wed, May 27, 2026, 7:05 PM UTC

cj wrote: post #215

> Coding agents really did change everything. These are tools which burn vastly more tokens The assumption here is that this is a positive thing. But this very well could end up being a major negative long term by increasing the cost per user, reducing margins. More usage = more cost = less profit. It's not obvious that more usage is good. It's only good if revenue per user increases more than cost does. I'm skeptica…

> It's only good if revenue per user increases more than cost does.

That's why it's so important for these labs that they're selling API tokens for more than the compute+energy costs needed to generate them.

Every indicator I've seen is that they do have a positive margin on that. If they don't, they're screwed.

Re: I think Anthropic and OpenAI have found product-market fit

#245

Post by _verandaguy » Wed, May 27, 2026, 7:06 PM UTC

simonw wrote: post #232

_verandaguy wrote: post #196

With respect to Simon, whose writing I've usually agreed with in the past and whose insights I've liked: this is a bad take that overlooks the extent to which corporations are imposing the use of AI on employees, and in particular ICs, who make up a majority of the AI-using workforce by headcount. Many of us are either openly having our performance reviews tied to AI use, especially at larger enterprises. Whether tha…

Are you saying that Anthropic's huge leaps in revenue are caused by stupid company policies and token leaderboards, and the moment companies stop imposing AI on their employees revenue will drop to a point where Anthropic are unlikely to be profitable? I don't think that's the case. I think the token leaderboard thing (which is clearly ridiculous) affects a tiny portion of companies and is already going out of fashio…

I'm saying that the truth lies somewhere in between, and that Anthropic's current revenue is being, in part, propped up artificially.

We're also in a place where a lot of the usage guidance around these tools is still nascent. People are cowboying a lot of stuff, even as larger companies start to organize AI policy/safety/responsible use working groups to try and policy around the shortfalls of the technology.

IMO: if this technology persists, and if we figure out a way to use it in a broadly safe way, the value proposition will probably trend down rather than up, at least on the code generation front.

As a research tool, it shows some promise, though I still find the ethics of the technology disgusting.

Re: I think Anthropic and OpenAI have found product-market fit

#246

Post by FuriouslyAdrift » Wed, May 27, 2026, 7:06 PM UTC

trjordan wrote: post #11

They've got, ballpark, $5t to $10t to make back in the next 5 years, or the hardware buildouts will start getting written down. This means we're going to need $1t+ per year in spending, per year, on tokens. 200m knowledge workers in the world, 30m developers. We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. 20% if you're a developer. That's a _huge_ shift. Most people…

I work for a tiny little company ($150MM annual rev with 9% net) and we are already looking at dropping $100k on hardware to run local models because, for us, they're "good enough."

Our estimated spend for AIaaS would exceed that cost in less than a year.

In a few years, there will be hardware capable of running frontier models good enough for most things at accessible prices for even tiny companies.

Re: I think Anthropic and OpenAI have found product-market fit

#247

Post by kansface » Wed, May 27, 2026, 7:06 PM UTC

simonw wrote: post #152

layer8 wrote: post #120

Earlier quoted context omitted.

Who pays for that value, and from what, if all knowledge workers lose their jobs? It sounds like the economy would largely reduce to the small minority class of independently wealthy people.

The more time I spend using agent tools the less I worry about knowledge worker job loss. It takes a skilled knowledge worker to use these things.

We'll get around to training job specific models or the equivalent. Thats just lower on the value chain for now.

Re: I think Anthropic and OpenAI have found product-market fit

#248

Post by Tuna-Fish » Wed, May 27, 2026, 7:06 PM UTC

materielle wrote: post #211

whatshisface wrote: post #173

Earlier quoted context omitted.

Here are a few thoughts: - The publicly available information about how inference costs compare to training costs is conflicted. EEs involved in datacenters talk about power usage spikes during training runs as if they were a major factor in the designs, but academic papers discussing cost-optimal scaling confidently treat inference-time compute as a major factor. - On the side of the balance indicating that training…

I'm about to leave a shallow comment, but I am a bit skeptical of the supposed drop in inference costs. If AI labs saw a lot of potential there, they'd surely be bragging about it non-stop? So the fact that publicly available information is conflicted is probably a sign that at the very least, the numbers aren't amazing. Yes I know there's no evidence and this is lazy reasoning. But there's probably a bit of truth to…

Why on earth would AI labs be bragging about how little the product they sell actually costs them to make? You don't want to do anything that reduces it's perceived value to the user, that might make them less willing to pay for it.

Also, inference costs are bound to go way down with more optimized architectures. GPUs are fundamentally not great at inference. No platform where the weights are streamed from a large pool of memory is. If the models ever quiet down, there will be massive step changes in cost/token, energy/token and tokens/second, as models are etched into silicon ala https://chatjimmy.ai/

Re: I think Anthropic and OpenAI have found product-market fit

#249

Post by hansmayer » Wed, May 27, 2026, 7:06 PM UTC

Legend2440 wrote: post #213

hansmayer wrote: post #175

Earlier quoted context omitted.

Well, it is a big news when the COO of Uber says it no? Not quite some small consultancy shop here.

But the COO did not say that. The headline was deliberately misrepresenting what he said.

No, he said exactly that, if you remove the corporate sanitised language designed to not offend the Uber CTO.

Re: I think Anthropic and OpenAI have found product-market fit

#250

Post by cogman10 » Wed, May 27, 2026, 7:06 PM UTC

roncesvalles wrote: post #226

cogman10 wrote: post #167

Earlier quoted context omitted.

This is the same argument that has been historically made for outsourcing developers. Get 20 more devs for the cost of 1 dev in the US. I suspect that AI will fail to pan out to the same extent for the same reason why outsourcing hasn't fully panned out (even though every company tries it after getting big enough). The problems that will come up will be and always have been ongoing maintenance. AI is great at writing…

Outsourcing of knowledge workers didn't work out because at large enough scales, the geographic arbitrage disappeared. Companies mostly always got what they paid for. The determinant of success was only whether the task needed American-tier labor or could make do with sub-American quality labor.

That's certainly part of it. But the other part that I've heard time and time again is that in order for outsourcing to be successful you basically needed an american engineer in the mix hand holding everything, clarifying requirements, and vetoing bad code.

That part of dev work, the requirements gathering, attention to details, clarifying requirements, is something AI also struggles with. A lot of companies basically waste time and money on outsourced devs because without a clear path forward they effectively will sit and do nothing, waiting for a prompt.