Nice job on this, it’s a really interesting approach. I’ve been developing an open-source coding agent over the past year, and RAG just wasn’t working at all. I switched to a repo map approach (which sounds similar to what aider is doing) and that helped a bit but still wasn’t great.

However, a few weeks ago I built an agent that takes in a new GitHub issue and is given a variety of tools to do research on the background information to complete the issue. The tools include internet searches or clarifying questions to ask the person who wrote the ticket. But the most useful tool is the ability to look at the codebase and create a detailed markdown file of various files, explanations of what each file does, relevant code samples or snippets from the files, etc..

It’s still early, but anecdotally I’ve seen a huge increase in the quality of the code that uses this research as part of the context (along with the repo map and other details). It’s also able to tackle much more complex issues than it could before.

I definitely think you’re on to something here with this wiki approach. I’ll be curious to dig in and see the details of how you are creating these. Here is my research code if you’re interested: https://github.com/jacob-ai-bot/jacob/blob/feature/agent/src...

And here’s an example of the research output (everything past the exit criteria section): https://github.com/kleneway/jacob/issues/62