Deep Agents is actively used in production by OpenSWE and LangSmith Fleet.
Overview
Key differences
LangChain Deep Agents:- Model flexibility: Swap model providers (Anthropic, OpenAI, or 100+ others) at any time and run evaluations.
- Long-term memory: Persist context across sessions and threads with the Memory Store
- Sandbox-as-tool pattern: Run individual operations in isolated sandboxes from different providers while the agent runs outside, or run the full agent inside a sandbox
- Virtual filesystem: Use pluggable backends (in-memory, disk, durable stores, sandboxes) for context and checkpoint management
- Production deployment: Deploy via
deepagents deployor self-host with the Agent Server - Observability: Use LangSmith for native tracing and debugging
- Standardize on Claude: First-class support for Claude models across Anthropic, Azure, Vertex AI, and AWS Bedrock
- Custom hosting: Build your own HTTP/WebSocket layer and run the SDK in containers
- Hooks: Easily intercept and control agent behavior
- Standardize on OpenAI: GPT-5.3-Codex and OpenAI-specific tooling
- OS-level sandbox modes: Use built-in
read-only,workspace-write, ordanger-full-accessmodes - MCP server mode: Expose your agent as an MCP server with
codex mcp-server - Observability: Use OpenAI Traces
Feature comparison
Notice a mistake?We drafted this comparison on March 4th, 2026.
If you notice mistakes or changes in products, please file an issue.
Connect these docs to Claude, VSCode, and more via MCP for real-time answers.

