[stevage]

The focus on upfront specs feels a bit off. Since it's apparently cheap to generate running code, as a user, I'd much rather be able to just iterate really fast and use output to refine my requirements rather than having to laboriously state them all up front. Agile rather than waterfall if you will.

[samus]

In that case, it might be easier to start over with fixed specs. That might not be as much work as it sounds like since most of the existing code would have been produced by the LLM, and only the human feedback and interventions would have to be redone. It would be almost like backtracking to an earlier point in a chat history and changing path there. TA talks about that another LLM could provide insight about where to change what.

It might also be possible to change an existing history without abandoning all which has happened afterwards. Of course, this could lead to conflicts, sort of like when rebasing a branch, and it would be useful to have another LLM look for it.

GPT Copilot might or might not be able to start from existing code as well and one would approach it as one would a legacy codebase that has to be adapted to new requirements.

[bsenftner]

It's the LLM that needs the upfront specs, regardless of what you'd like, at this point. If that is the case, implement a nondestructive composable system, like node based visual editors - ComfyUI for example. Change the upfront specification "node" and let the LLM cascade through that and any attached nodes creating the code (or whatever) fresh each time.