[devsoul]

Here are some of the tools which you may like:

- GitHub Copilot - CodeSee - Sourcegraph - Swimm - GitLoop - bloop - Codex Atlas

If I could ask an AI one question about a codebase to help onboard developers, it would be:

What are the main architectural patterns and dependencies in this codebase, and how do they interact with each other?

[vinaypanghal]

That’s a great list—thanks for sharing! Tools like Github CoPilot have been game-changers for me when it comes to simple tasks codebases. I’ve heard a lot about GitLoop recently, curious to hear your experience with it—does it handle large repositories well?

[devsoul]

Indeed copilot is a game changer and they are now going to bring spark which will make a huge difference.

GitLoop is well-equipped to handle large repositories, providing tools that streamline code analysis and management, it does improves productivity and code quality. Also, it can efficiently processes large and complex repositories by using optimized algorithms and cloud-based infrastructure to ensure fast and accurate analysis without impacting your development workflow.

[vinaypanghal]

We've built a tool to do the same. We started with a use case of triaging CVEs and SAST findings but our focus has always on accuracy of results. Its been pretty challenging to make a highly accurate reasoning and retrieval engine and I don't think the problem is already solved yet.

In your opinion, is there anything that any of these tools don't already do well?