Why LangGraph.js Over Plain LangChain?

The Problem with Linear Chains

LangChain's core abstraction is the chain — a linear sequence of steps. That works for straightforward tasks like "summarize this document" or "answer a question from context." But real-world AI agents need something more.

Consider a customer support agent that needs to:

1. Classify the intent
2. Route to the right handler
3. Maybe call external APIs
4. Decide if human escalation is needed
5. Loop back if the user has follow-up questions

This isn't a linear chain. It's a graph.

Enter LangGraph.js

LangGraph.js models your agent as a state machine — a directed graph where:

• Nodes are functions that process and update state
• Edges define the flow, including conditional branching
• State is a typed, reducible object shared across nodes

const workflow = new StateGraph(SupportState)
  .addNode("classify", classifyIntent)
  .addNode("handle_billing", handleBilling)
  .addNode("handle_technical", handleTechnical)
  .addNode("escalate", escalateToHuman)
  .addEdge("__start__", "classify")
  .addConditionalEdges("classify", routeByIntent, {
    billing: "handle_billing",
    technical: "handle_technical",
    complex: "escalate",
  });

Three Reasons to Choose LangGraph.js

1. Explicit Control Flow

With plain LangChain, complex routing requires nested callbacks or custom chain classes. With LangGraph.js, routing is a first-class concept:

function routeByIntent(state: SupportState): string {
  if (state.intent === "billing") return "handle_billing";
  if (state.intent === "technical") return "handle_technical";
  return "escalate";
}

2. Built-in Persistence

LangGraph.js checkpointers save state after every node execution. This means your agent survives server restarts, supports multi-turn conversations, and enables time-travel debugging.

3. Human-in-the-Loop

Need a human to approve before the agent takes action? LangGraph.js has first-class interrupt() support — pause the graph, wait for human input, then resume exactly where you left off.

When to Use What

Learn More

Our LangGraph.js Mastery course takes you from zero to production-ready agents across 36 lessons, with hands-on coding exercises and real-world projects.