7 Checks to Run Before Trusting AI-Generated Code

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. A small bug fix can unexpectedly become a refactor, dependency update, configuration change, and formatting sweep.

Start with:

git status
git diff --stat
git diff

git diff --stat gives you an immediate picture of the scope.

Suppose you asked the agent:

Add validation to the email signup endpoint.

You expected changes in two files. But the diff says:

12 files changed, 437 insertions(+), 186 deletions(-)

Stop there.

Before examining whether the code works, ask why the task required hundreds of changed lines.

While reviewing the diff, look specifically for:

• files unrelated to the task
• deleted tests, disabled validation, and new configuration values
• permission changes
• changes to dependency files
• large refactors hidden inside a feature
• duplicated helper functions and error handling that ignores failures

The goal is simple: make sure the AI solved the task you gave it rather than a larger task it invented.

2. Making the Compiler, Linter, and Type Checker Judge It

Humans are terrible compilers.

Do not spend ten minutes visually checking syntax that a deterministic tool can check in seconds.

python -m compileall .
ruff check .
mypy .

For example: