[mocamoca]

I get pretty good results by writing specs and prototype with a LLM, through more or less managed conversations.

But once the prototype is done, I spend too much time refining the details, fixing everything going wrong (bas design details, wrong implementation, half done testing ...)

A full agentic setting would be too expensive for me (I wonder how much Garry tan spends...)

So I'd like to take a more balanced approach with: 1. usual LLM specs and prototyping to get the bases of the feature and boilerplate done 2. Write myself the code, with the help of an ai auto complete (this is Where I look for recommendations) 3. Use a setup as OP mentioned to review code

[RevEng]

Cursor with its tab completion. Iterate with the agent part to research, design, and plan. Let it generate boilerplate and scaffolding, perhaps with placeholders for you to fill in. Then fill in as you normally would, but with an auto-complete that uses all of your code and design docs and everything else to inform that completion rather than the limited set of info that shows up in an LSP.

I believe JetBrains IDEs have something similar too, but I don't have as much experience using theirs since my employer hasn't blessed their AI tools yet.