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AI coding assistants can accelerate development but require careful oversight and shouldn't be blindly trusted. Like overconfident junior developers, they excel at small tasks but struggle with architecture, dependencies, and context. Clean, modular codebases help AI perform better, while legacy systems often lead to misinterpretations. Common pitfalls include superficial fixes, brittle test cases, and reinforcing poor design patterns. Developers should review AI-generated code thoroughly, break tasks into smaller steps, maintain quality control through team processes, and set realistic expectations about productivity gains.

Treat Your AI Assistant Like an Overconfident Junior Developer

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