A hotel booking agent that books 15 guests into a 10-person room. One that makes up occupancy numbers the database never had. One that picks the wrong tool out of 29 and burns tokens on every call. These are not prompt problems you can word your way out of. They need structural fixes. In this hands-on workshop you build five of them yourself, on a hotel booking agent. Pull answers from a structured source so the agent computes instead of guessing. Narrow a crowded tool list down to the few that match the request. Add a second and third agent that check the work before the user sees it. Keep your rules in code the agent cannot bypass. And let it correct its own near-misses instead of dead-ending. Each one is live code with before and after numbers, and a final part on taking them to production. You leave with working Python, a way to pick the right fix for each failure, and an open source repo. No cloud account or cost needed, sandboxes are provided.

Outline: • Introduction - Why AI Agents Hallucinate Differently Than LLMs • Demo 00 - Strands Agents Primer • Demo 01 - Graph-RAG vs. Standard RAG • Demo 02 - Semantic Tool Selection • Demo 03 - Multi-Agent Validation • Demo 04 - Neurosymbolic Guardrails • Demo 05 - Agent Control Steering • Demo 06 - Production on Amazon Bedrock AgentCore • Workshop Recap + Resources • Q&A