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To better understand how and why AI-assisted software development can go wrong, we’ve outlined a classification system for common failure modes that occur when developers work with large language models. These error classes highlight specific breakdowns. By identifying where responsibility typically lies, this framework helps teams provide more targeted feedback, improve collaboration, and ultimately produce more reliable software. What follows is a breakdown of five key error types, each illustrating a different kind of failure and who is responsible.