AI coding assistants can generate a large amount of working code in a few minutes. This increases productivity but it also makes them dangerous. Bad AI-generated code does not necessarily look bad. It may compile, pass tests, and use clean variable names while still making the wrong assumption about an API, authorization rule, edge case, or dependency. GitHub warns that AI-generated code can be semantically incorrect and recommends carefully reviewing and testing it before merging. So instead of asking "Does this AI-generated code look good?", run these 7 checks .

Does this AI-generated code look good?

1. Inspecting the Diff Before Running Anything

Your first check should not be ChatGPT, Copilot, Claude Code, or another model.

It should be Git.

When coding agents are given access to an entire repository, they sometimes modify more than the task requires.…