# What's the difference between the Claude Agent SDK and LangGraph?

The Claude Agent SDK wraps the Claude Code binary as a library and runs only Claude, which decides for itself which built-in tool to call next; LangGraph is a low-level, model-agnostic runtime where you define the nodes, the edges between them, and one shared state object by hand, mixing deterministic steps with LLM-driven ones in the same graph. Delegation looks different as a result: the Claude SDK spawns a subagent for a focused subtask, one level of its own implicit loop, while a LangGraph agent is only as complex as the graph you build, matching Claude's simple loop only if you chose to draw it that way.

LangGraph's own distinctive piece is checkpointing: state is persisted after every node, so [a run that fails partway through re-invokes from the checkpoint just before the failing node instead of starting over](/answers/langgraph-evals/how-do-i-replay-a-failed-langgraph-run). The Claude Agent SDK has sessions that resume or fork between conversations, but nothing checkpoints progress inside a single run. Tracing splits along a similar line: LangGraph's native path is LangSmith, while the Claude Agent SDK's OpenTelemetry spans are still behind a beta flag and use Claude Code's own names rather than the GenAI ones.

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Sources:
- Claude Docs: Agent SDK overview: https://code.claude.com/docs/en/agent-sdk/overview (fetched 2026-09-27)
- LangGraph documentation: Overview: https://docs.langchain.com/oss/python/langgraph/overview (fetched 2026-09-27)

Source: https://tessary.ai/answers/claude-agent-sdk-evals/whats-the-difference-between-the-claude-agent-sdk-and-langgraph
More on Claude agent sdk evals: https://tessary.ai/answers/claude-agent-sdk-evals
From Tessary, agent reliability for AI agents in production: https://tessary.ai