LangChain Simplifies Production AI Agent Deployment with Managed Deep Agents

LangChain

Jun 10, 2026

LangChain introduced Managed Deep Agents in private beta, an API-first hosted runtime for its open-source Deep Agents. This offering aims to streamline the operational complexities of deploying autonomous AI agents, allowing developers to focus on agent behavior rather than managing infrastructure.

LangChain launched Managed Deep Agents in private beta, an API-first hosted runtime for its open-source Deep Agents harness. It offers durable execution, checkpointing, sandboxed tool access, and over 30 endpoints for managing agents. Definition files are stored and versioned in LangSmith.

Availability: Private beta
API Endpoint: /v1/deepagents
Endpoints: 30+ for agents, integrations, connections, triggers, threads, runs
SDKs: Chat, streaming, Human-in-the-Loop (HITL)
Context Management: Context Hub
Observability: LangSmith tracing

Deploying long-running AI agents in production demands significant infrastructure for memory, tool access, and observability. This offering packages that operational layer, allowing teams to avoid building custom runtime infrastructure. Companies like Google Managed Agents and Claude Managed Agents offer similar solutions.

Managed Deep Agents supports workflows like support, research, and coding agents needing persistent context and artifact generation. The service is available through an API for programmatic creation and management. Access is currently via a private beta waitlist.

View the full update on langchain.com

LangChain

@LangChain13h ago

Managed Deep Agents is built to handle real-world interactions: 30+ endpoints for agents, integrations, connections, triggers, threads, and runs Purpose built task queues to handle bursty traffic SDKs for chat, streaming, and HITL https://t.co/gK3ToNTO1C

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