AI agents love type errors

When AI coding agents develop backend systems, they operate iteratively: writing code, collecting feedback, reviewing results, and adjusting until no errors surface — meaning any undetected issues get shipped to production. Type errors represent the strongest feedback mechanism for backend agents because they occur at compile time, pinpoint exact code locations, and specify expected versus actual types. They are economical to generate since a type check runs quickly and deterministically without database setup or deployment overhead.