LangGraph

## How LangGraph compares

LangGraph is one of several multi-agent / orchestration frameworks in this directory; they differ by control model:

| Framework | Model | Open source | Notable for |
| --- | --- | --- | --- |
| **LangGraph** | Graph of nodes/edges with explicit state | Yes | Fine-grained, controllable stateful workflows |
| **CrewAI** | Role-based agent "crews" | Yes | Quick multi-agent setups by roles and tasks |
| **AutoGen** | Conversational multi-agent | Yes | Agents that collaborate via message passing |

Choose LangGraph when you need explicit control over state and branching; CrewAI for fast role-based teams, or AutoGen for conversation-driven agent collaboration.

## Editorial notes

LangGraph is an open-source orchestration framework from the LangChain team for building stateful, multi-step agent workflows as graphs. Instead of a single prompt-response call, you model an agent as nodes (steps and tools) and edges (control flow), with shared state threaded through the graph — which makes branching, loops, retries, and human-in-the-loop checkpoints explicit and controllable.

It is model-agnostic and works with Claude models as the reasoning layer, so you can build durable, inspectable agent systems on top of Claude. The graph model supports persistence and checkpointing, which helps with long-running or resumable workflows.

Reach for LangGraph when a linear prompt chain is not enough and you need state, branching, and controllable execution for non-trivial agents. For simple one-shot tasks it is more structure than you need.

## Disclosure

Editorial listing. No paid placement or affiliate link is used.