Briefing

Conceptual Guide Deep Agents The runtime behind production deep agents

ai-dev

Deploy Deep Agents harness using LangSmith Deployment and Agent Server to enable durable execution, memory, HITL, and observability for production agents.

What to do now

Configure LangSmith Deployment with Agent Server, set up PostgreSQL persistence, enable durable execution, memory checkpoints, and human‑in‑the‑loop for your Deep Agents.

Summary

Deep Agents is a production‑ready harness that builds on LangSmith Deployment (LSD) and the Agent Server to provide durable execution, memory, human‑in‑the‑loop, and observability for long‑running agents. The runtime primitives include durable execution with task queues and checkpointing, short‑term and long‑term memory stored in PostgreSQL, guardrails, middleware, multi‑tenancy, authentication, agent authentication, RBAC, streaming, concurrency control, tracing, sandboxed code execution, MCP, A2A, webhooks, and cron jobs. The Agent Server exposes assistants, threads, runs, memory, and scheduled jobs via a REST API, while LSD manages the underlying infrastructure. Durable execution ensures that agents survive crashes, deploys, and long pauses for human approval by persisting state and resuming from the last checkpoint. Memory is split into short‑term (per thread) and long‑term (per user/organization) to support context across conversations.

The guide maps each production requirement to a runtime capability, illustrating how Deep Agents can be shipped as a package that developers can deploy without reinventing core infrastructure. It emphasizes the need for observable, durable, and multi‑tenant agent systems that can be controlled by operators and users alike.

Key takeaways include the comprehensive set of runtime primitives, the separation of short‑term and long‑term memory, and the use of PostgreSQL for persistence and semantic search.

Key changes

  • Deep Agents harness built on LangSmith Deployment (LSD) and Agent Server
  • Runtime primitives include durable execution, memory checkpoints, guardrails, middleware, multi‑tenancy, auth, agent auth, RBAC
  • Supports human‑in‑the‑loop interrupt/resume
  • Provides streaming, concurrency control, tracing, code execution sandboxes
  • Integrates MCP, A2A, webhooks, cron jobs
  • Runtime uses PostgreSQL for persistence
  • Multi‑tenancy isolates user data via auth middleware
  • Agent Auth handles OAuth token storage for third‑party services

Affects

enterprise

Source angles · 2 perspectives

LangChain Blog
Independent angle

The Runtime Behind Production Deep Agents

Open
LangChain Blog
Independent angle

Evaluating Deep Agents: Our Learnings

Open

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