I may be biased because I work on an AI powered enterprise productivity product, but while I agree they have PMF right now, I wonder whether people's use will evolve in ways that undercut the current PMF. Chatting with an assistant is great if there's no product with tailored UI available that also has the AI capabilities. But once there is, I suspect people may switch, or more importantly enterprises may switch because they'll get the benefits of AI without the clunkiness of a chat only interface. We may see another DOS -> GUI-like shift.

More specialized products will consume tokens but their builders will be incented to optimize token use and switch models as costs and capabilities change. And if search engines become more AI capable, and Google is clearly striving for this, then they may have pressure from two sides that could squeeze the number of use cases for AI chat. AI coding isn't going anywhere and nor is the need for AI in general but I wonder if the products will have to evolve significantly to maintain the current levels of PMF. And then there's the question of profitability...

I think it's fair to say they had achieved product-market fit when their revenues were growing deep triple digits month over month. What we're seeing now is that perhaps they have achieved profitability or at the least a more sustainable balance sheet.

So it largely sounds like many more people will be able to write software - and will use AI to do it. Existing software engineers will continue to automate their tasks away like they always did, but perhaps at a faster rate.

The impact of AI in other fields seems to be muted.

If those companies found PMF we should expect to see the effects of all those tokens burned on the products we all know and use. In my own experience: yes new features can be delivered much more quickly (by orders of magnitude) but knowing what to build and how to evolve a product with taste and direction does not; so ultimately the user-facing gains are marginal.

I suspect that once the technology has been tamed and the hardware and software has been commoditized, the impact will be much less dramatic than we expect and we will realize the importance of a shared vision, experience, taste, intuition and discernment in building good products.

> but as far as I can tell those credit costs are an exact match for the API token costs listed for those models.

it is only true for USD. for example if you pay in euro, this is actually more expensive. kind of makes no sense, because it translates to $1 = €1

Product-market fit, but what about customer retention?

It is quite trivial to switch from using one model or another. Likewise, in a few years we'll have affordable laptops to run today's frontier models.

What's their plan to let us keep subscribing?

"[would have spent] $1,199 with Anthropic, $980 with OpenAI"

How many tokens is that, input/output-wise?

(a) I'm curious if you feel like you got $2000 worth of value out of them in the last month?

(b) I'm also curious if you would have gotten similar quality out of a slightly lower-cost provider of an open-weight model? (e.g. Kimi K2.6 and DeepSeek v4 Pro) and what the spend would have been for that.

I myself have managed to spend not quite $4 on OpenRouter and have felt it was very worth it; I just have much smaller, or more targeted requests I guess. (Lately, adding features to a static site generator in Python, or setting up log forwarding via a docker compose file)

  Input tokens:        52,545,485
  Output tokens:        5,767,253
  Cache create tokens:  5,112,029
  Cache read tokens: 1,475,069,465
  Total tokens:      1,538,494,232
  Total cost:        $1,199.79

  Input tokens:          52,598,013
  Output tokens:          4,681,867
  Reasoning output:       2,091,063
  Cached input tokens: 1,153,844,864
  Total tokens:        1,211,124,744
  Total cost:          $980.37

The end game here is going back from a model where a bunch of product and tech management people sit in the U.S. or Europe, and try to manage thousands of mediocre talent sitting somewhere far away. The new model is you give those coding tools to good engineers colocated with your product people, and you ship good stuff much faster. If you can achieve such a setup, the token costs can be $50k per seat per month and you still run circles around the legacy IT models in terms of efficiency. Giving everyone the API keys and not changing the way products are managed is not going to work.

I see two really good ideas for monetizing the free tier for consumers.

Firstly, if the user is asking for things where AI can link to products or services to buy, there's a very good relevancy, much higher than in other types of ads.

Secondly, since the AI often takes time to compute answers to user's questions, they could be shown ads while waiting. People could perhaps be less annoyed by this than some other commercials since they know the break has to be there anyway.

(First idea is something I came up when asking Claude to compare some products, or ask for help in lawn care. Second idea was by a colleague.)

If we define product market fit as profitable with a trillion dollar valuation, I think the term has lost its helpfulness.

I do agree with the author that these companies seem much stronger financially recently though.