LangGraph: Build Production AI Agents (The Pattern 57% of Companies Use)

Description

Basic agent loops work for demos. They break in production. 57% of production AI agent deployments use LangGraph. Klarna runs it for 85 million users. AppFolio uses it across their entire platform. Why? Because LangGraph gives you what basic loops can't: - State management that survives crashes - Conditional routing based on agent decisions - Human-in-the-loop approvals - Checkpointing and recovery In this video, I build a production-ready LangGraph agent from scratch. You'll learn: - How LangGraph's graph model works (nodes, edges, state) - How to build conditional routing (agents that make decisions) - How to add persistence (state that survives restarts) - How to build agents that can pause for human approval We build a Research Agent that can search, analyze, and write reports - with human approval before publishing. LINKS: AI Developer Masterclass (Waitlist): https://bit.ly/ai-dev-wait AI Guild Community:🚀 https://bit.ly/ai-guild-join 🚀 Free AI Newsletter: https://bit.ly/ai-dev-wait Code: https://github.com/pdichone/vincibits-langgraph-production-agents Join the AI Guild Community: 🚀 https://bit.ly/ai-guild-join 🚀