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exceptione 4 hours ago  [ - ]

  > - a code map strategy on a big repo. Per file: summary, when_to_use, public_types, public_functions. This is done per file and saved until the file changes. With a concurrency of 32, I can usually code-map a huge repo in minutes. (Typically Flash, cheap, fast, and with very good results)
Thanks, but why use any AI to generate this? I would say: you document your functions-in-code, types are provided from the compiler service, so it should all be deterministically available in seconds iso minutes, without burning tokens. Am I missing something?
jeremychone 3 hours ago  [ - ]

Very good point. I had two options:

1) Deterministic

  - Using a tree-sitter/AST-like approach, I could extract types, functions, and perhaps comments, and put them into an index map.

  - Cons:

    - The tricky part of this approach is that what I extract can be pretty large per file, for example, comments.

    - Then, I would probably need an agentic synthesis step for those comments anyway.
2) Agentic

  - Since Flash is dirt cheap, I wanted to experiment and skip #1, and go directly to #2.

  - Because my tool is built for concurrency, when set to 32, it's super fast.

  - The price is relatively low, perhaps $1 or $2 for 50k LOC, and 60 to 90 seconds, about 30 to 45 minutes of AI work.

  - What I get back is relatively consistent by file, size-wise, and it's just one trip per file.
So, this is why I started with #2.

And then, the results in real coding scenarios have been astonishing.

Way above what I expected.

The way those indexes get combined with the user prompt gets the right files 95% of the time, and with surprisingly high quality.

So, I might add deterministic aspects to it, but since I think I will need the agentic step anyway, I have deprioritized it.