The use of AI assistants by junior developers has changed the code review process for senior engineers. While AI generates clean, well-formatted code with proper documentation, it often masks underlying logic errors that are harder to detect than the messy code previously written by juniors.
Senior developers now face an increased workload, as they must often re-verify the logic behind AI-generated solutions. For example, when configuring Nginx for SSE endpoints, AI might suggest settings like proxy_buffering off and proxy_read_timeout 3600s, which can have unintended side effects on server performance and connection handling.
To address these challenges, the author suggests changing submission requirements. Juniors should provide clear assumptions, testing methods, and rollback plans alongside their code. Small pull request sizes and verbal explanations of the logic without AI assistance are recommended to ensure the developer truly understands the solution.
The author notes that AI tools should not be banned, as they significantly boost productivity for experienced engineers who know how to verify the output. The focus should shift toward teaching junior developers how to validate AI-generated results effectively.
