Cloudlflare builds OAuth with Claude and publishes all the prompts

Yeah, my bad, I got lost and frustrated while scrolling endlessly and trying to keep track of what was part of what. Look, clearly you are happy with the results, so all good for you.

It literally says in the post it’s not “vibe coded”. That has a very specific meaning of not reviewing the code at all and accepting everything.

> Question is: will this work for non-greenfield projects as well?

Depends on the project. Word on the street is the closer your project is to an archetypical React tutorial TODO App then you'll likely be pleased with the results. Whereas if your project is a WDK driver in Rust where every file is a minefield then you'll spend the next few evenings having to audit everything with a fine toothed comb.

> since AI will rewrite it

That depends if you believe in documentation-first or program-first definitions of a specification.

Well, what they were doing before was sure as shit not going to get them an iPhone.

Just because a paradigm shift doesn't miraculously catapult us all into a post-scarcity economy overnight, that doesn't mean it's not an important milestone on a longer road.

1) Any companies that host APIs using open-weights models (LLama, Gemma, Deepseek, etc) in exchange for money. There's a lot of them around, at different scales and different parts of a hosting provider's lifecycle. Check for example the Openrouter page for any open-weights model for hosters of that model with price data.

2) (API) platform power having no value in this space has been demonstrated repeatedly. There are no network effects, because you can't use the user data to improve models. There is no lock-in, as the models are easy to substitute due to how incredibly generic the interface is. There is no loyalty, the users will jump ship instantly when better models are released. There is no purchasing power from having more scale, the primary supplier (Nvidia) isn't giving volume discounts and is actually giving preferential allocations to smaller hosting providers to fragment the market as much as possible.

Did you have some other form of platform power in mind?

3) I did not concede that point because I don't think it's relevant. They provide the exact data for their R1 inference economics:

- The cost per node: a 8*H800 node costs $16/hour=$0.0045/s to run (rental price, so that covers capex + opex).

- The throughput per node: Given their traffic mix, a single node will process 75k/s input tokens and generate 15k/s output tokens.

- Pricing ($0.35/1M input when weighing for cache hit/miss, $2.2/1M output)

- From which it follows that the per-node revenue is $0.35/(1M/75k/s) = $0.026/s for input, and $2.2/(1M/15k/s)=$0.033/s for output. That's $0.06/s in revenue, substantially higher than the cost of revenue.

Like, that just is what the economics of paid R1 inference are (there being V3 in the mix doesn't matter, they're the same parameter count). Inference is really, really cheap both in absolute cost/token terms and relative to the prices people are willing to pay.

Their aggregate margins are different, and we don't know how different, because here too they choose to also provide free service with no ads. But that too is a choice. If they just stopped doing that and rented fewer GPUs, their margins would be very lucrative. (Not as high as the computation suggests since the unpaid traffic allows them to batch more efficiently, but hat's not going to make a 5x difference.)

But fair enough, it might be cleaner to use the straight cost per token data rather than add the indirection of margins. Either way, it seems clear that API pricing is not subsidized.