I recently tried to use Serena (an AI coding agent + language server toolkit) and hit a crash during project indexing. Instead of filing a vague issue, I set up Claude Code, indexed Serena’s own codebase using Serena itself, and then asked the AI agent why Serena was failing.

This led to an interesting discovery: • My initial guess (“large files causing crashes”) was wrong. • The actual problem was that Serena’s language servers struggled with complex regex/iterator-heavy files. • I was able to file a much better issue report, with logs and a hypothesis, and propose an improvement (exclude certain files from indexing).

This seems like a useful workflow for open-source contributors: use AI-assisted analysis responsibly before submitting issues, to save maintainers time and avoid noisy back-and-forth.

Here’s the write-up: Why Half-Baked Bug Reports Waste Everyone’s Time (and How AI Can Level Up Your Open-Source Contributions) (replace with final blog link)

Curious if others are using Claude/Serena for similar “meta-debugging” workflows. Would love to hear examples.