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A safety review layer for AI code
Sego is a local-first review layer for AI-generated code.
Sego is a local-first review layer for AI-generated code. It sits after tools like Cursor, Claude Code, Codex and Copilot, reviews staged changes, and produces structured findings for security risks, unexpected changes and risky AI-generated diffs.
Hi Product Hunt,
I built Sego because AI coding tools are making code generation faster, but the review step is still painful.
For solo builders, vibe coders and small teams, the question is often not “can AI write the code?” but “is this code safe enough to commit?”
Sego is a local-first review layer for AI-generated code. It reviews staged changes, catches risky patterns, and saves structured review artifacts.
I am looking for the first 20 AI coding users. If you use Cursor, Claude Code, Codex, Copilot or Lovable, I would love to run a free Sego audit on a small AI-generated project or diff.
Website: https://sego-8dw.pages.dev/
GitHub: https://github.com/007M7/Sego-Agent
Would love your feedback.
About A safety review layer for AI code on Product Hunt
“Sego is a local-first review layer for AI-generated code. ”
A safety review layer for AI code was submitted on Product Hunt and earned 0 upvotes and 2 comments, placing #38 on the daily leaderboard. Sego is a local-first review layer for AI-generated code. It sits after tools like Cursor, Claude Code, Codex and Copilot, reviews staged changes, and produces structured findings for security risks, unexpected changes and risky AI-generated diffs.
On the analytics side, A safety review layer for AI code competes within SaaS, Developer Tools, GitHub and Tech — topics that collectively have 1.2M followers on Product Hunt. The dashboard above tracks how A safety review layer for AI code performed against the three products that launched closest to it on the same day.
Who hunted A safety review layer for AI code?
A safety review layer for AI code was hunted by 007M7. 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 A safety review layer for AI code including community comment highlights and product details, visit the product overview.
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