Refactoring

What is refactoring?

Refactoring is the "the code works, but it's a mess — let's tidy it" step. The behavior doesn't change at all; you just clarify names, split big functions, and pull out duplicated code. It's like cleaning your room: everything's the same stuff, but now you can actually find it. AI refactoring hands that tedious, fiddly work to a model.

Why is "don't change behavior" the whole point?

Refactoring isn't adding features
Its only goal is clearer, easier-to-change code, so the before and after must behave identically. Your tests should stay green the whole time.
Accidental changes are bugs
Tweak the logic by mistake and a customer might see it break. That's why "equivalent transformation" is the iron rule.

What can AI refactor?

Better names
Turn a, b, tmp into meaningful variables, and vague function names into clear ones.
Split big functions
A hundreds-of-lines monster can be broken into small functions by responsibility.
Kill duplication
When the same logic appears in several places, AI pulls it into one shared function.
Loosen dependencies
Reduce coupling between modules so changing one spot doesn't ripple everywhere.

When to do it — and when not to

Refactor when code gets harder to read and one change touches many places. But don't refactor for its own sake — if a feature needs to ship now and there are no tests to catch you, restructuring at scale is risky.

Bottom line: refactoring changes structure, not behavior — and AI lets you do the tidying fast and safely.