Deploying agentic systems requires more than algorithmic innovation—you need robust verification, fallback mechanisms, and human-in-the-loop safeguards to handle real-world failure modes at scale.
This tutorial bridges the gap between agentic AI research and real-world deployment, covering how LLM-based systems that reason, plan, and use tools are moving from labs to production. It shares practical lessons from pharmaceutical and financial deployments, including design patterns, failure modes, and safety strategies like verification pipelines and human oversight.