I think Anthropic and OpenAI have found product-market fit

All the planned infrastructure commitments. At least for OpenAI I think they're supposed to spend $300+bn in the next few years.

GPUs are driven really hard plus they use up a ton of energy and water, they cost a ton to run.

Sounds like mostly-baseless praise for the LLM behemoths / capital investment black holes.

> I currently subscribe to the $100/month Max plan from Anthropic and the $100/month Pro plan from OpenAI

... which already indicates a bias.

> If you are a heavy user of coding agents these plans are a fantastic deal... that’s $2,180.16 worth of tokens for $200—not bad at all!

Thank you for the sales pitch. Perhaps go buy a car and tell us how [insert your manufacturer] has "found product-market fit"?

> Anthropic are strongly rumored to be about to have their first profitable quarter.

First, the strong rumor is a claim by Anthropic itself. But even assuming that's true - it's an "operating profit", i.e. disregarding the massive capital expenses for years, and may also disregards ongoing capital expenses, if those happen not to be taken this particular quarter.

> 1 Trillion .. companies spending $200+/month/user will get you there a whole lot faster

First note the use of the first person plural to talk about Anthropic and OpenAI.

But that aside - most companies aren't paying $200 USD/user-month. But even if they were - if we take the 30 Million SW developers mentioned in trjordan's comment as subscribers, that's 2400/user-year * 30 Million = 72 Billion USD / year. And this is already rather optimistic, but - want to double that number of subscribers? Fine, make it 150 Billion / year. Still not there with a rosy outlook and assuming the hype and enthusiasm continue for many years.

And those rosy estimates are more likely than not unrealistic. I am reminded of this review of some empirical research regarding the benefit of LLM/AI use:

https://cmr.berkeley.edu/2025/10/seven-myths-about-ai-and-pr...

I mean, Western providers such as Fireworks AI/Microsoft Foundry (US) or Tensorix (EU) already are offering many of these models on their own hardware with all the typical compliance boxes ticked through a standard API. Either as open weight models or through partnerships with Chinese firms, or both. DeepSeek etc. do not have to do anything here other than making their models available to Western partners (either as open weights or through a licensing agreement).

I see you trying really hard to make things right and are everywhere in the comment. I feel a bit bad in formulating my comments a bit polemical.

Also my highest respect for responding so calmly without lowering your debating level to mine. I try to best to explain what I think is wrong.

To start I didn’t interpret the article as a burn.

I think it’s interesting to explain what’s wrong with it, because it seems similar to what‘s wrong with AI. The issues are subtle.

- Anthropic doesn’t have a profitable quarter, it’s financial engineering (https://www.wheresyoured.at/anthropics-profitability-swindle...)

- The first argument about your subscription price, doesn’t has anything to do with the overall claim of the article. It would if at all be a weak argument to support the opposite. Subsidizing prices signals a lack of PMF.

- That you hire sales people after you had a billions of funding is nothing surprising and doesn’t indicate PMF or not.

- AI Implementations are fresh and of course AI Failures are thin, but so are AI successes. I haven’t seen any companies creating billions of shareholder value because they’ve massively invested in AI and their competitiors didn’t You really can look at these things in 5 to 10 years and it is multi-faceted including cultural acceptance.

- That they need to buy more compute to satisfy the requests is probably the strongest argument in the artical, but don’t conclusive. The product is been sold heavily subsidized and in hype cycle. And again both OPENAI and Anthropic have to show growth in order to justify the IPO.

- Regarding the part about revenue I refer to the linkedm article above, as it does explain it very well.

The conclusion is reasonable given the arguments, but not the title.

However it is missing all the real discussion points that are actually in observation at the moment.

Local models as alternatives, IPO finanical engineering, how AI implementation actually will perform over years... Let’s all not forget crypto. It’s been full of "use cases" just a bunch of years ago. I like the idea of crypto(btc,eth) and I’m still invested, but 99.99% of coins have died on promies.

So this is not a piece of critical thinking, but this reads like a twitter thread to sell me a course :/