"Can you replay all of your prompts exactly the way you wrote them and get the same behaviour out of the LLM generated code? In that case, the situation might be similar. If that's not the case, probably not." Yes and no. It's possible in theory, but in practice it requires control over the seed, which you typically don't have in the AI coding tools. At least if you're using local models, you can control the seed and have it be deterministic.

That said, you don't necessarily always have 100% deterministic build when compiling code either.

That would be interesting. I don't believe getting 100% the same bytes every time a derivative work is created in the same way is legally relevant. Take filters applied to copyright protected photos - might not be the exact same bytes every time you run it, but it looks the same, it's clearly a derivative work.

So in my understanding (not as a lawyer, but someone who's had to deal with legal issues around software a lot), if you _save_ all the inputs that will lead to the LLM creating pretty much the same system with the same behaviour, you could probably argue that it's a derivative work of your input (which is creative work done by a human), and therefore copyright protected.

If you don't keep your input, it's harder to argue because you can't prove your authorship.

It probably comes down to the details. Is your prompt "make me some kind of blog", that's probably too trivial and unspecific to benefit from copyright protection. If you specify requirements to the degree where they resemble code in natural language (minus boilerplate), different story, I think.

(I meant to include more concrete logic in my post above, but it appears I'm not too good with the edit function, I garbled it :P)