Looking at the code, it does have some sort of automatic discovery. I also don't know how scalable Claude Code is. I've spent over a decade thinking about code search, so I know what the limitations are for enterprise code.

One of the neat tricks that I've developed is, I would load all my backend code for my search component and then I would ask the LLM to trace a query and create a context bundle for only the files that are affected. Once the LLM has finished, I just need to do a few clicks to refine a 80,000 token size window down to about 20,000 tokens.

I would not be surprised if this is one of the tricks that it does as it is highly effective. Also, yes my tool is manual, but I treat conversations as durable asset so in the future, you should be able to say, last week I did this, load the same files and LLM will know what files to bring into context.

FWIW Claude code conversations are also durable. You can resume any past conversation in your project. They're stored as jsonl files within your `$HOME/.claude` directory. This retains the actual context (including your prompts, assistant responses, tool usages, etc) from that conversation, not just the files you're affecting as context.

Excellent, I look forward to trying it out, at minimum to wean off dependency to Claude Code and it's likely current state of overspending on context. I agree with looking at conversations as durable assets.

It greps around the code like an intern would. You have to have patience and be willing to document workflows and correct when it gets things wrong via CLAUDE.md files.