Deep agents can reason through multi-step tasks, use tools, and manage long-running workflows, but getting them from prototype to production introduces real challenges around state management, multi-tenancy, error handling, and safety. In this talk, I'll break down the architecture behind Deep Agents and LangSmith Deployment, the production primitives that make them reliable (checkpointing, sandboxing, middleware for rate limiting and PII), and the patterns we've seen work across enterprises scaling agentic systems. You'll walk away with a practical playbook for taking your agents from "works in my demo" to production-ready.