AI coding agents are generating production code at an unprecedented rate, but most teams are reviewing that code with practices designed for a world where humans wrote every line. This mismatch is creating hidden risk at scale, and the gap between perceived quality and actual quality grows wider with every release.
This book provides a practical framework for building review systems that work for AI-generated code. You'll learn why traditional code review falls short, how AI-generated code fails in fundamentally different ways, and how to design a hybrid review architecture that combines static analysis, AI-powered review, and targeted human judgment.
Inside, you'll discover:
• How to build a layered review pipeline that catches defects at every stage
• The specific quality standards you need for reviewing AI-generated code
• How to decide which changes need human review and which can be fully automated
• Ways to configure AI review tools to produce actionable feedback your team trusts
• How to measure review effectiveness and continuously improve your pipeline
• Strategies for building custom review agents for your specific codebase
• The security implications of AI-generated code and how to mitigate them
The era of reviewing every line of code is ending. This book shows you how to review the right things at the right level of abstraction, using automation for what automation does best and human judgment for what only humans can evaluate. Stop applying old practices to new problems.
