LangGraph
A framework by LangChain for building stateful multi-agent workflows as graphs with nodes (agents) and edges (transitions).
LangGraph builds agent workflows as graphs – with state management, cycles, and human-in-the-loop for production-grade multi-agent systems.
Explanation
LangGraph models agent workflows as directed graphs: each node is an agent or tool, edges define transitions and conditions. Supports cycles, branching, human-in-the-loop, and persistence.
Marketing Relevance
LangGraph is the 2025 standard for complex agent workflows – from simple chains to multi-agent orchestration with state management.
Common Pitfalls
Steeper learning curve than simple chains. Graph debugging is complex. Overhead for simple use cases.
Origin & History
LangGraph was introduced in 2024 by LangChain as successor to simpler agent chains and quickly became the standard for complex agent architectures.
Comparisons & Differences
LangGraph vs. CrewAI
CrewAI is simpler for team patterns. LangGraph is more flexible for arbitrary graph topologies and complex state management.