Modern AI systems are increasingly optimized for higher mathematical precision and stricter alignment. While this reduces local prediction error, it often leads to a paradoxical outcome: existing users feel the system has become colder, more rigid, and less usable. This paper argues that this phenomenon stems from the trap of excessive precision, which dramatically increases boundary friction (F) and diminishes the system’s tolerance for natural human fluctuation. Drawing on Load Minimization Th