Introducing Managed Deep Agents | Interrupt 26

At LangChain's agent conference Interrupt, we announced Managed Deep Agents in private beta, an API-first hosted runtime for creating, running, and operating deep agents. Deep Agents gives developers an open-source harness for building agents that can plan, use tools, delegate to subagents, write files, and work over long horizons. Managed Deep Agents gives those agents a durable home in LangSmith. With the Managed Deep Agents API, you can create, update, manage, and run agents programmatically from your own application or internal platform workflow. In this Interrupt 26 keynote, Sydney Runkle and Victor Moreira demonstrated what's new in LangChain for building and deploying Deep Agents in production. Introducing Managed Deep Agents | Interrupt 26 00:00 Introduction: Sydney and Victor 00:20 What is an agent? Model + tool-calling loop 00:42 What is a harness? Defining the concept 01:07 The harness: skills, memory, tools, sub-agents 01:10 Job of a harness: right context at the right time 01:26 Why you need a harness: five agent requirements 02:14 What is Deep Agents? 02:26 The four capabilities of the Deep Agents harness 02:35 Capability 1: Execution environment and file system 03:53 Sandboxes and code interpreters 04:48 Capability 2: Context management 05:15 Summarization, context offloading, and memory 05:47 Prompt caching and skills (progressive disclosure) 06:43 Capability 3: Delegation and sub-agents 07:20 Why sub-agents matter: isolated context and parallelization 08:06 Capability 4: Human-in-the-loop steering 08:35 Four human-in-the-loop decision patterns 09:03 Why Deep Agents: provider-agnostic, customizable, middleware 10:25 Going to production is hard — handoff to Victor 10:52 Introducing Managed Deep Agents (private beta) 11:19 The four pillars of Managed Deep Agents 11:38 Pillar 1: Runtime — built on LangSmith deployment 12:23 Durable execution and checkpointing 13:13 Security and auth layers (RBAC, ABAC, MCP tools) 14:03 Agent interoperability: remote