How to review AI generated PRs (thoughtbot.com)

As AI tools become increasingly integrated into software development, teams face the challenge of reviewing AI-generated pull requests (PRs) that may contain excessive code and less coherent logic. In an insightful discussion, the complexities of reviewing such code are addressed, emphasizing that foundational review goals—like achieving code quality and maintainability—remain valid, whether the code is human-written or AI-generated. Reviewers are encouraged to pick their battles wisely, remain open to different coding approaches, and recognize that AI may not fully understand existing system architectures, which can lead to unnecessary reimplementations. The author highlights the importance of maintaining a collaborative review process, suggesting that reviewers remain engaged and provide specific, constructive feedback while being conscious of the potential for AI tools to influence PR authoring. Key technical considerations include ensuring that tests are meaningful, assessing edge cases, and streamlining code to leverage existing systems effectively. Ultimately, the conversation stresses that addressing poor-quality AI-generated code is a broader people and process issue that requires clear expectations and collective effort for continuous improvement within development teams.