Phase 4: Multi-Agent Systems · 70 min · Python · LangGraph · Anthropic SDK

LangGraph for Stateful Multi-Agent Workflows

A workflow that can't resume from failure isn't production-ready.

Hiring signal: LangGraph is the dominant framework for production multi-agent workflows in 2026. It appears in job postings at Stripe, Notion, Replit, and most enterprise AI teams. The ability to build checkpointed, human-in-the-loop workflows in LangGraph is a concrete, testable skill that hiring managers look for.

What you will learn

Build a LangGraph StateGraph with typed state, nodes, and conditional edges
Implement checkpointing with a SQLite persister for fault-tolerant workflows
Add interrupt/resume logic for human-in-the-loop approval gates

The Problem

Ad-hoc multi-agent systems have a critical flaw: they hold all state in memory. One server restart, one API timeout, one process kill — and the entire workflow must restart from scratch. For tasks that take minutes or hours, this is unacceptable. LangGraph solves this with a graph-based execution model that persists state after every node, enabling checkpointing, resumption, and human-in-the-loop approval gates.

LangGraph is not just a convenience library. It's an architectural decision: your workflow's state is a first-class citizen that survives failures.

LangGraph Core Concepts

StateGraph: a directed graph where each node is a function that receives the current state and returns updates. Nodes don't communicate directly — they read from state and write back to state.

State: a TypedDict (or Pydantic model) that flows through all nodes. Think of it as a shared whiteboard: every node can read anything on it, and write its results to specific fields.

Nodes: Python functions or agent calls. Each node signature is (state: State) -> dict. The dict it returns is merged into the state.

Edges: connections between nodes. A normal edge always flows forward. A conditional edge routes to different next nodes based on the current state.

Checkpointer: a persistence backend (SQLite, Postgres) that saves state after each node completes. This is what enables resumption after failure.

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers Typed State Design, Checkpointing and Human-in-the-Loop, Build It, What to Practice — plus a hands-on lab, quiz, and project artifact.

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Key terms in this lesson

Agent