GoKawiilAnalysis pinpoints why LLM tools fail: models draft forms, humans just rubber-stamp them
A technical breakdown argues that failures in LLM-powered tools trace back to three root causes tied to how forms and prompts are filled: missing values, incorrect conditions, and misread intent. It explains that as language models increasingly draft the contents of forms themselves, human oversight has quietly shifted from checking correctness to simply approving whatever is presented, since a fabricated value looks identical to a verified one.