I asked AI to fix a bug. It confidently returned a modified file. I ran it. A different bug appeared. Sound familiar? It's like asking a confident stranger for directions in an unfamiliar city. The intent is genuine. The accuracy is a separate question. The Stack Overflow Developer Survey (2025) found that 66% of developers say AI-generated code is "almost right, but not quite," and 45% report that debugging AI-generated code takes more time. AI excels at producing plausible code. It does not excel at asking "under what conditions will this code break?" So what if we gave AI the thinking patterns that human debuggers use? That's what this article does: 10 debugging techniques, compressed into 5 prompt blocks you can copy into CLAUDE.md or any agent skill definition. Why AI Jumps to "Plausible Fixes" Tell AI "the API returns a 500 error." Most of the time, it adds a try-catch or null check. Sometimes the symptom disappears.…