Build an AI Code Review Agent in GitHub Actions (That Actually Reduces Incidents

Build an AI Code Review Agent in GitHub Actions (That Actually Reduces Incidents) A production-grade GitHub Actions workflow + an SRE reliability rubric that transforms AI from a code suggester into a structured risk detection system. We tried AI code review in CI. It was fast. It was confident. It was mostly noise. It praised trivial refactors. It nitpicked formatting. It occasionally hallucinated “critical issues.” And it did absolutely nothing to reduce production incidents. The mistake wasn’t using AI. The mistake was asking AI to “review code.” In reliability engineering, we don’t ask: “Is this code good?” We ask: What is the blast radius? What is the rollback plan? What happens under failure? What is the operational risk? So we rebuilt our AI reviewer using SRE principles. This is the exact system. 🚨 Why Most AI Code Review Systems Fail Most implementations: • Run LLM over a PR diff • Ask for general feedback • Post suggestions as a comment The result? Unstructured opinions. But