Deep Agents Explained

Join LangChain's Sydney Runkle and Jake Broekhuizen as they dive into Deep Agents, an open source agent harness built for long-running tasks. It handles planning, context management, and multi-agent orchestration for complex work like research and coding. In this talk, Sydney and Jake break down the core components of the Deep Agent "harness"—including planning tools, sub-agent delegation, file system integration, and secure execution environments (sandboxes). They also discuss the very real challenges of deploying these agents to production, managing context windows, and keeping track of long-running traces using LangSmith. Deep Agents: Building for Complex, Long-Running Tasks with LangChain 00:00 Introductions 01:32 What are Deep Agents? 02:43 Common Use Cases for Deep Agents 03:56 Core Components of a Deep Agent 05:53 How File Systems Work in Deep Agents 11:58 Agent Skills and Skill Sharing 14:15 Sandboxes and Execution Environments 17:21 Challenges in Deploying Agents to Production 19:18 Observability, Tracing, and LangSmith 21:01 Quick Tips for Getting Started 25:05 Q&A: How to Write a Good Prompt 26:23 Q&A: Multi-Agent Architectures and Sub-agents 28:13 Q&A: Sandboxing, Isolation, and Cost Efficiency 29:43 Q&A: Will Deep Agents Replace Deterministic Workflows? 30:52 Q&A: Supporting Multiple Providers and Multi-modal Blocks Extra resources - Build with LangChain: https://www.langchain.com/ - Get started with Deep Agents: https://www.langchain.com/deep-agents - Trace and Evaluate with LangSmith: https://smith.langchain.com/