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description: A conference talk by a Red Hat security engineer covering how to handle AI-generated code contributions in open source and enterprise settings. It opens with...
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# "Looks Good to Me": A Practical Guide to Handling AI-Generated Code - Roman Zhukov

**[NDC Conferences](https://daily.dev/sources/ndc)** · 60 min read · 0 upvotes · 0 comments

## Summary

A conference talk by a Red Hat security engineer covering how to handle AI-generated code contributions in open source and enterprise settings. It opens with real-world examples of AI bots autonomously submitting PRs and fake vulnerability reports, then proposes four pillars: clear AI contribution policy, secure AI coding guidelines, automation/quality gates, and accelerated vulnerability triage. Practical recommendations include publishing a short AI coding policy (60–130 words), using OpenSSF secure AI coding guides, adopting tools like PQSS anti-slop for PR filtering and AI-assisted code review skills catalogs, and leveraging AI for vulnerability triage as CVE report volumes grow exponentially. The talk emphasizes that AI tools make code generation cheap but not code review, and that deterministic automation should not be replaced wholesale by AI.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=LnZDY6XC5pA>

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---

Tags: [#security](https://daily.dev/tags/security), [#open-source](https://daily.dev/tags/open-source), [#ai-coding](https://daily.dev/tags/ai-coding), [#ai-assisted-development](https://daily.dev/tags/ai-assisted-development)

[View this post on daily.dev](https://daily.dev/posts/looks-good-to-me-a-practical-guide-to-handling-ai-generated-code---roman-zhukov-ktkzl4uqv)

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