Your anti-hallucination tricks look great on your laptop: the agent pulls precise answers, blocks bad operations, and catches made-up data. Then you ship, and the notebook falls apart: hardcoded keys, data that only lived in memory, no way to see what happened, and a custom search index nobody wants to maintain. The hard part of a reliable agent is not the technique, it is making the technique survive production. This talk takes five anti-hallucination techniques from a demo to a deployed agent: pulling answers from a structured source instead of guessing, routing to the right tool without a custom index, keeping your rules in a database so you change a limit in seconds without shipping new code, letting the agent fix its own near-misses, and checking results across more than one agent. You see them run together on a hotel booking agent, against real hallucination attempts and rule violations. You leave with the whole architecture you can deploy yourself, not just the ideas.

Outline: • The Prototype-to-Production Gap • Semantic Tool Routing via MCP Gateway • Steering Rules in DynamoDB • GraphRAG in Production • Full Production Test • Resources + Q&A