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LineageLens
AI wrote it. LineageLens proves it.
Been deep in AI-assisted dev work and kept hitting the same wall: something breaks in AI-generated code and there's no way to answer "which prompt wrote this, which model, and what was the context?" Root cause analysis becomes guesswork. Built LineageLens to fix that. It runs a local proxy on port 8788 that sits between your AI tools and their providers. Every time an AI writes ≥4 lines into your codebase, it captures the exact prompt, the model and tool that produced it (Cursor, Claude Code)
Top comment
Hey Product Hunt! 👋 I built LineageLens because I kept running into the same frustrating moment — something breaks in AI-generated code and there's zero record of what prompt produced it, which model wrote it, or what context surrounded the decision. Git blame tells you who committed it. It doesn't tell you what the AI was asked. LineageLens fixes that by sitting between your AI tools and their providers via a local proxy. Every insertion of 4+ lines gets captured with the full prompt, model identity, session context, and risk signals — automatically, across Cursor, Claude Code, Copilot, Aider, Continue, and 6 more tools. The part I'm most excited about: the MCP server. Once wired into Claude Code or Cursor, you can ask "what prompt wrote this auth function?" or "which files have the highest AI risk density?" directly inside your chat — no tab switching, no reconstructing context from memory. Everything is self-hosted. Your prompts and code never leave your infrastructure. Would love brutal feedback from this community — what's missing, what's confusing, and whether this solves a problem you've actually felt. Happy to answer any questions below.
About LineageLens on Product Hunt
“AI wrote it. LineageLens proves it.”
LineageLens launched on Product Hunt on May 14th, 2026 and earned 56 upvotes and 1 comments, placing #80 on the daily leaderboard. Been deep in AI-assisted dev work and kept hitting the same wall: something breaks in AI-generated code and there's no way to answer "which prompt wrote this, which model, and what was the context?" Root cause analysis becomes guesswork. Built LineageLens to fix that. It runs a local proxy on port 8788 that sits between your AI tools and their providers. Every time an AI writes ≥4 lines into your codebase, it captures the exact prompt, the model and tool that produced it (Cursor, Claude Code)
On the analytics side, LineageLens competes within Design Tools — topics that collectively have 260k followers on Product Hunt. The dashboard above tracks how LineageLens performed against the three products that launched closest to it on the same day.
Who hunted LineageLens?
LineageLens was hunted by Praveen. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of LineageLens including community comment highlights and product details, visit the product overview.