AI coding tools can make many edits quickly. Without version control, it can be hard to tell what changed or restore a working version. GitHub provides a history of project changes and a safer way to review updates.
Save a known-good starting point
Before asking an AI assistant to change a project, commit or back up the current working version. Use a short message that explains the state of the project.
Make one focused change
Give the assistant a specific task and constraints. For example, improve mobile navigation without changing authentication or payment code. Smaller changes are easier to review and test.
Review the difference
Inspect changed files before accepting the work. Check for deleted configuration, unexpected dependencies, hard-coded test URLs, exposed keys, and unrelated edits.
Test before deploying
Run the build and test the changed feature along with nearby user journeys. A successful build does not prove every interaction works. Keep deployment separate from code generation when possible.
Recover when something breaks
Use repository history to identify the last known-good version and revert the specific bad change. Avoid overwriting the only copy of working code.
- Back up the project.
- Ask for one focused change.
- Inspect the diff.
- Run tests.
- Commit the verified version.
- Deploy after review.
Version control gives you a clear record of progress and a practical way to experiment without making every AI suggestion irreversible.