Coding with AI tools

Stage 6 · Lesson 4 of 6

Symptom patches versus root causes

Debugging with AI

A makes the error go away without fixing the bug: an empty catch block that swallows the exception, a null check that quietly skips the work, a retry loop around a failing call, a disabled lint rule, a longer timeout. AI tools reach for these because they satisfy the request "make the error stop".

The bug is still there and now fails silently somewhere worse. A fix changes the code where the problem actually starts. Ask yourself: why did this value become null, why is this call slow, why does this run twice?

Keep asking why until the answer is something you can change. Then keep the failing test from your reproduction as a test, so the bug cannot come back unnoticed.

Common trapdeclaring victory because the symptom stopped.

A question to check yourself, an AI practice session and 2 cheat sheet entries come when you add the roadmap to your account. Add it

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