32k tokens is 500-1000 lines of code, so more like thousands of dollars, unless you're comparing against a landing page or CRUD tool arranged through Upwork. On the flip side, before I dove into AutoGPT I couldn't get GPT-4 to iterate on something as simple as a TypeScript function that deeply converts { foo_bar: string } to { fooBar: Date } without running out of context and cyclically reintroducing regressions.

Only if you can get that result in one pass.

The real utility of LLMs is that they can be called in a loop to scan through many web pages, many code files, issue tickets, emails, etc...

There are already demos and experiments out there that for every input, 4x outputs are generated, then those are fed back into the LLM 4x for "review", then the best variant is then used to generate code which then automatically tested, errors are fed back in a loop, also with 4x parallel tries, etc...

It's the throughput compared to humans that is the true differentiator. If hooking up the API in a loop up ends up costing more than a human, then it's not worth it.