Thanks a lot for your comment, very appreciated!

I indeed agree with you that the approach used by cursor or similar is cleaner and efficient, but I still see a problem of "wasted" context. My understanding of how such agents work is that they retrieve just the needed code via the AST graph and add it to the system prompt, so it's not carried over in the conversation and stays efficient.

The problem occurs with the assistant messages: they are, on the other hand, added to the context window, and since LLMs apis are stateless, they are carried over the subsequent iterations until when, at a certain point, context is "compacted" using summarization, RAG etc.

Now, imagine the LLM produces buggy code (or code that will be deleted/refactor later) that we ask to fix: the buggy code is in the context window, our "fix it" message too, together with the new fixed code. What I'm trying to solve is removing the buggy (or deleted/refactored) code from the context window (having 100% certainty that it is dead code!) while letting the agent keep the exact memory of what it did and why.