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Chapter 12

Debugging With AI

Every program you build will break. That is not a sign you are doing it wrong — it is the normal state of software. Bugs are not a failure of skill; they are what happens when real code meets real data, real users, and real cases nobody imagined. The difference between a frustrating afternoon and a five-minute fix is method. When you debug by vibe coding, you are not the one staring at the stack trace until it makes sense — the stack trace being the error report your program prints when it crashes, which we'll unpack later. You are the director: you reproduce the problem, gather the right evidence, and hand the AI a tight, well-framed case so it can do the heavy lifting. This chapter gives you a repeatable process for exactly that — one that works whether the bug is a one-line typo or a tangled race condition three layers deep. (A race condition is a timing bug: two things happen in an order you didn't expect, like two people grabbing the last seat at once.)

  1. 12.1The core mindset
  2. 12.2A debugging checklist
  3. 12.3Feeding the AI the right context
  4. 12.4Reading errors you don't understand
  5. 12.5Hypotheses, logging, and binary search
  6. 12.6Root cause versus symptom
  7. 12.7When the AI goes in circles
  8. 12.8Understanding the fix before you keep it
  9. 12.9The takeaway
  10. 12.10Recap and Practice

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