About this resource
LangGraph is designed for more explicit control than a simple chain can offer. It works well when you need state, review steps, recoverable execution, or multi-step agent logic.
Capabilities
- Graph-based control flow
- Stateful execution
- Good for human-in-the-loop systems
Use cases
- Multi-step assistants
- Supervised agent execution
- Escalation and review loops
Getting started
- Model the workflow first
- Add state persistence early
- Test the failure and resume paths
Strengths
- Excellent for advanced orchestration
- Makes state explicit
- Supports robust production patterns
Considerations
- Requires more architecture thinking
- Overkill for simple single-step assistants
Questions
Is LangGraph only for agents?
It is best known for agents, but the graph model works for any stateful AI workflow.
Do I need LangChain to use LangGraph?
No. Many teams use them together, but LangGraph can stand on its own.