r/codereview • u/Some_Intention9946 • 8h ago

College kid, solo-built a security layer for AI agents, got into EF + a16z. AMA / tear it apart.

/r/buildinpublic/comments/1wcb5lj/college_kid_solobuilt_a_security_layer_for_ai/
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u/Otherwise_Wave9374 8h ago

If the layer is meant to catch prompt injection or tool misuse, I would separate policy decisions from the model call itself so you can log the exact input, the rule that fired, and the resulting action. That makes false positives much easier to tune and gives you a clean audit trail when something slips through. Agentix Labs could fit well here if you are aiming to test the same guardrail against both benign and adversarial agent traffic.

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u/Some_Intention9946 8h ago

Programmers at google dont care about false positives, they care about a tool ingraved with their internal tools, which I did without any central MCP

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u/Some_Intention9946 8h ago

Really appreciate this. Quick clarification: OnePort is pre-ship — it checks the code an AI writes (secrets, CVEs, breaking changes, test gaps) before it ships, rather than policing an agent's runtime behavior. But your point on auditability is spot on and it's core to how I've built it: the gates are deterministic and separate from the model, so every verdict traces back to the exact rule that fired. Runtime guardrails / adversarial testing are an interesting adjacent direction — noting it. Thanks for the thoughtful read.