Show HN: Building an AI That Understands Your Code

A couple of years ago, I noticed a gap in developer workflows. We have amazing tools for writing and shipping code, but understanding someone else’s code—especially in large repositories—often feels like solving a mystery without a map. What if there was an AI that could explain codebases as easily as a teammate would?

That idea led to TuringMind, an AI-powered code chat platform that helps developers onboard faster, explore unfamiliar repositories, and even triage vulnerabilities. It’s designed to be your go-to tool for understanding and reasoning about code—whether you’re debugging, reviewing, or just trying to figure out why the previous dev left a maze of if-else statements.

In late 2022, I started working on the foundation: enabling the AI to provide meaningful, context-aware answers to questions about code repositories. Over time, it evolved into a platform that integrates seamlessly with GitHub, analyzes repositories using LLMs, and delivers insights tailored to the way developers think.

Now, TuringMind is live and helping developers:

Answer complex questions about code dependencies and structure. Onboard to new teams or projects faster by understanding repository context. Triage vulnerabilities by reasoning about false positives and code impact. Next up is expanding TuringMind’s capabilities to automate even more tedious tasks, like triaging common CVEs or suggesting architectural improvements.

Let me know what you think of the idea! Are there pain points in your workflow where TuringMind.ai could help? Would love to hear your feedback or ideas for improvement.