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Notes -
I'm also not allowed to use the best models for my job, so take my advice (and, well, anyone else's) with a grain of salt. Any advice you get might be outdated in 6 months anyway; the field is evolving rapidly.
I think getting AI help with a large code base is still an open problem. Context windows keep growing, but (IMO) the model isn't going to get a deep understanding of a large project just from pasting it into the prompt. Keep to smaller components; give it the relevant source files, and also lots of English context (like the headers/docs you mentioned). You can ask it design questions (like "what data structure should I use here?"), or for code reviews, or have it implement new features. (I'm not sure about large refactors - that seems risky to me, because the model's temperature could make it randomly change code that it shouldn't. Stick to output at a scale that you can personally review.)
The most important thing to remember is that an LLM's superpower is comprehension: describe what you want in the same way you would to a fellow employee, and it will always understand. It's not some weird new IDE with cryptic key commands you have to memorize. It's a tool you can (and should) talk to normally.
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