LangGraph Verified
Key insights
Concrete technical or product signals.
- Choose LangGraph when your assistant must loop, branch, or pause for approvals rather than single-pass chains.
- Pairs naturally with LangChain primitives—teams already on LangChain adopt fastest.
Use cases
Where this shines in production.
- Customer-support agents with tool loops and escalation states
- Research agents that revisit retrieval based on intermediate results
- Workflows requiring checkpointing and resume after failures
Limitations & trade-offs
What to watch for.
- More moving parts than simple LCEL chains—budget for testing state transitions and observability.
- Rapid ecosystem evolution; pin versions and run integration tests on upgrades.
Models referenced
Declared model dependencies or integrations.
GPT-4o, Claude 3.5 Sonnet
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LangGraph FAQ
What is LangGraph?
LangGraph is a library for building stateful, cyclic agent and workflow graphs on top of LangChain—suited to multi-step tools, human-in-the-loop approvals, and durable execution patterns that go beyond linear chains.
When should teams use LangGraph?
Customer-support agents with tool loops and escalation states
What should teams watch out for with LangGraph?
More moving parts than simple LCEL chains—budget for testing state transitions and observability.
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