Comment by danielbln
2 months ago
I would suggest using an agentic system like Cline, so that the LLM can wander through the codebase by itself and do research and build a "mental model" and then set up an implementation plan. The you iterate in that and hand it off for implementation. This flow works significantly better than what you're describing.
> LLM can wander through the codebase by itself and do research and build a "mental model"
It can't really do that due to context length limitations.
It doesn't need the entire codebase, it just needs the call map, the function signatures, etc. It doesn't have to include everything in a call - but having access to all of it means it can pick what seems relevant.
Yes, that's exactly right. The LLM gets a rough overview over the project (as you said, including function signatures and such) and will then decide what to open and use to complete/implement the objective.
In a real project the call map and function signatures are millions of tokens themselves.
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1k LOC is perfectly fine, I did not experience issues with Claude with most (not all) projects around ~1k LOC.
Actual projects where you'd want some LLM help start with millions of lines of code, not thousands.
With 1k lines of code you don't need an LLM, the entire source code can fit in one intern's head.
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I guess people are talking about different kinds of projects here in terms of project size.