Refactoring With AI Only When You Have Tests

Refactoring means changing how code is written without changing what it does. AI is great at it: condensing loops, extracting helpers, renaming variables. But the only way to *prove* the behavior didn't change is to run tests after.

Some examples

• You ask Claude to refactor a 40-line function into smaller pieces — then run your test suite to confirm green.
• You let Cursor rewrite a class to use composition over inheritance, with tests as the safety net.
• You skip a refactor on untested legacy code because there's no way to verify nothing broke.
• You ask ChatGPT to rewrite a function and write tests *first* before accepting the refactor.

Try it!

Find a small function in your project. Write 3 tests. Then ask AI to refactor. Confirm tests still pass.

Practice this safely

Try this with a school, hobby, or family example where the stakes are low. Use the AI output as a draft you can question, not as the final answer.

1. 1Ask AI to explain safety net in plain language, then underline anything that sounds uncertain or too broad.
2. 2Give it one detail from "Refactoring With AI Only When You Have Tests" and ask for two possible next steps plus one reason each step might be wrong.
3. 3Check refactor against a trusted source, teacher, adult, expert, or original document before you use it.