I think the product market fit is still how you interface with increasingly powerful AI. Right now is Codex/Claude code, and they just added computer use/web browsing into them. The product is the speed at which you can interface it and to be able to serve it with infrastructure.

Traditional product market fit isn't really applicable with tech evolving so fast.

Is PMF enough. It is such a dynamic self-disrupting wave that it is like predicting physical chaos. These aren't early Googles in a blue ocean. Maybe a blue ocean full of pirates and dragons!

This isn't me being a doomer I just don't know. Can we look at Q2 profits and draw hockey sticks yet?

Remember people are boasting how much their expenses are. That is where we are in the bubble/new paradigm.

My Costs without CC Max+Caching over past 2 months: $112K.

Ran `ccusage` on my Claude Code logs.

- Total tokens: 22.2B

Without current Claude deals, my personal cost would have been *~$112,000*.

I think we are overly fixating on Anthropic and OpenAI.

Since there are lots of models that are competitive and have a much better pricing, both OpenAI and Anthropic seem inefficient. I don't get why someone would want to buy shares after IPO apart from fomo and artificially built enthusiasm.

Anthropic and OpenAI may well be the Altavista and the Yahoo of the AI age.

For an alternate albeit somewhat contrarian view, also see Ed Zitron’s piece that add context to Anthropic’s profitability: https://www.wheresyoured.at/anthropics-profitability-swindle...

TL;DR Ed argues that the deal between Anthropic and xAI could have been negotiated in such a way as to make Anthropic only appear profitable during its “ramp-up” period in June, which incidentally is also the month that Anthropic is making tons of other pricing changes.

I wonder how a focus on per-token API profits will impact the incentives to improve token efficiency and drive down costs through optimized compute. I suppose as long as a few leading labs are competing, we'll see progress in this regard, but it's certainly less in their interest than it is with a flat subscription pricing model.

Article doesn’t mention on-prem and on device models. Almost guaranteed that there are a range of killer enhancements on these fronts waiting to drop until IPOs get closer to inflict maximum chaos on the valuation games.

While the big guys will argue they’re worth trillions expect others to drop chaos booms showing their NPV may be effectively zero.

Just to be clear, enterprise companies are using the enterprise option for security/auditing/enforcement reasons, not because OpenAI or Anthropic forbids them from buying a 200$/month plan for each engineer, right? Do they have any clause forbidding using those individual plans in a company?

Not sure I can agree with this. Sure, we have enterprise paying, but are we actually getting anything new and interesting made from LLMs compared to if we just didn't have them at all?

Maybe acceleration in smaller teams. We still seem in the era of the early internet where what questions LLMs change hasn't exactly emerged.

What baffles me is the range of estimates.

Operating profit is both post depreciation and fees paid to third parties for hire. So aside from shenanigans like RSUs and financing interest that's already somewhat close to actual economics.

Meanwhile we've got commenters here talking of 5-10 trillion with a T revenue shortfall.

Those are very different takes on reality