TL;DR : An LLM is like Don Quijote—you can't cure his madness, it's stochastic by nature. The solution isn't to fix the madman but to assign him a deterministic Sancho Panza as a sidekick. MDD consists of two layers: first, you study the errors it makes to design tools that absorb those mistakes, and then you let it loose with those tools to verify you've closed any gaps. Design for madness, not against it. I spent weeks auditing logs. 165 sessions of an AI agent interacting with a CLI to manage tasks. Over 500 errors. 370 retries. Patterns emerged, repeating over and over: the agent would use --status when the flag was actually called --state . It would write Todo when the API expected unstarted . It would pass urgent as a priority when the system only accepted numbers. And what fascinated me was that every single error made sense. They weren't random. They were plausible . Exactly the kind of mistakes you or I would make if we "kind of" understood a domain but had never read the documentation carefully.…