This is really interesting; ive done very high level code maps but the entire project seems wild, it works?
So, small model figures out which files to use based on the code map, and then enriches with snippets, so big model ideally gets preloaded with relevant context / snippets up front?
Where does code map live? Is it one big file?
So, I have a pro@coder/.cache/code-map/context-code-map.json.
I also have a `.tmpl-code-map.jsonl` in the same folder so all of my tasks can add to it, and then it gets merged into context-code-map.json.
I keep mtime, but I also compute a blake3 hash, so if mtime does not match, but it is just a "git restore," I do not redo the code map for that file. So it is very incremental.
Then the trick is, when sending the code map to AI, I serialize it in a nice, simple markdown format.
- path/to/file.rs - summary: ... - when to use: ... - public types: .., .., .. - public functions: .., .., ..
- ...
So the AI does not have to interpret JSON, just clean, structured markdown.
Funny, I worked on this addition to my tool for a week, planning everything, but even today, I am surprised by how well it works.
I have zero sed/grep in my workflow. Just this.
My prompt is pro@coder/coder-prompt.md, the first part is YAML for the globs, and the second part is my prompt.
There is a TUI, but all input and output are files, and the TUI is just there to run it and see the status.