LLMs fail in predictable ways:
- Hallucinations: inventing functions or libraries that don't exist
- Outdated patterns: using deprecated APIs from old training data
- Plausible nonsense: code that looks correct but has subtle bugs
- Missing context: not knowing about your specific project structure
Recognizing these patterns helps you catch problems before they ship.