5 Practical Code‑Quality Controls to Guard AI Coding Agents
As AI coding agents like Claude Code, Cursor, and Codex become common in development pipelines, this article outlines five concrete quality‑control mechanisms—feedback sensors, semantic evaluations, refactor boundaries, provenance trails, and agent surface inventories—detailing tools, trade‑offs, and suitable scenarios to ensure generated code is trustworthy before entering a pull request.
