A Layered Review Model for AI-Generated Code

AI-generated code changes review dynamics because code volume rises while traditional pull-request practices either miss important risks or slow teams unnecessarily. This article argues for a layered review model in which machines enforce form through linting, tests, security, compliance, and AI-specific checks, while human reviewers focus on architectural fit, trust boundaries, error handling, and requirement-level correctness. It also distinguishes where AI reviewers help and where they create noise. Engineering leaders should redesign review workflows around automation plus intent-based human oversight if they want to scale AI-assisted delivery without weakening quality.