The default failure mode of AI debugging is a plausible fix for the wrong cause. The antidote is to make Claude reproduce the bug before proposing any change — explain the exact sequence that produces it, or write a failing test that captures it. That forces Claude to commit to a specific theory you can check, converting 'here is a guess' into 'here is the mechanism'. Once the reproduction is right, the fix usually follows cleanly, and you trust it because it addresses a cause you have seen confirmed.

Two hypotheses beat one

For a bug that resists the first fix, ask Claude for two competing explanations and the observation that would tell them apart. This stops it latching onto the first plausible cause and turns debugging into a short experiment: run the test that distinguishes them, and you know which is real. Give it the actual error and the relevant code slice, not the whole repo — burying the signal in noise makes Claude's job harder, not easier.

Frequently asked

How do I debug effectively with Claude?

Make it reproduce the bug before fixing — explain the exact cause or write a failing test — so it commits to a checkable theory instead of a plausible guess. The fix then follows cleanly.

Why does Claude fix the wrong thing?

Because it jumped to a plausible fix without confirming the cause. Requiring a reproduction first, and giving it the real error rather than a description, keeps it on the actual bug.

What if Claude's first fix doesn't work?

Ask for two competing hypotheses and the observation that distinguishes them, then test. That narrows to the real cause instead of trying fixes at random.