Blind Spots in LLMs for AI Coding
This article highlights several blind spots the author encountered while using Large Language Models (LLMs) for AI coding. Issues include insufficient black-box testing, stateless tools, over-reliance on automation, and neglecting documentation. Solutions suggested include preparatory refactoring, using static types, keeping files small, and adhering to specifications. The author hints at future Cursor rule suggestions to address these problems.