Most AI agent demos work beautifully. Then they hit real users, real data, and real edge cases — and start booking the wrong meetings, leaking context, or looping forever on a task they can't finish. The gap between "impressive demo" and "dependable system" is almost never the model. It's the guardrails around it. This is a practical guide to why agents fail once they leave the demo, and the concrete controls that make them safe to run in production. Why demos lie A demo is ...