With the increasing use of AI coding assistants, code review meetings are facing new challenges. Developers often cannot fully explain why AI-generated changes were made, leading to superficial reviews. This post explores how to restructure code review sessions to focus on understanding AI decisions, verifying correctness, and maintaining team accountability. It suggests preparing structured summaries of AI contributions before meetings and shifting the review focus from line-by-line checks to higher-level design and logic validation. For engineering teams adopting AI tools, this is a practical operational concern that affects code quality and team dynamics.
As AI tools generate more code, traditional code review meetings need to evolve. This post discusses challenges and suggests new approaches.