Coding agents: silent hooks vs. loud hooks for AI code quality

A developer explains two types of hooks for AI coding agents: silent-fix hooks that auto-correct output, and fail-loudly hooks that block errors and teach the agent. For complex rules like Flyway migration naming, silent fixes are less correct because they lack context. The post argues that fail-loudly hooks improve agent learning by surfacing mistakes in context.