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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.
I'm really happy that some friends are paying attention to my project. Honestly, sego is only at the minimum MVP stage right now. I am looking for a technical partner and VC investment. If you're interested, you can follow along. Currently, sego has detailed PRD documents, technical workflows, and a business plan. Today I fixed some of sego's technical debt issues. If you're interested, you can use sego. If you have any questions, please submit an issue directly, and I will reply as soon as possible. Thank you all for your support!
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.
A safety review layer for AI code was featured in SaaS (43k followers), Developer Tools (515.4k followers), GitHub (41.3k followers) and Tech (627.5k followers) on Product Hunt. Together, these topics include over 313.8k products, making this a competitive space to launch in.
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.
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