Building Production AI Agents with LangGraph

About this course

Building Production AI Agents with LangGraph: A Complete Hands-On Course

Learn how to build production-ready AI agents with LangGraph through a practical, hands-on journey from fundamentals to advanced agent architectures.

This course focuses on the engineering concepts you need to move beyond simple LLM demos and build AI agents that are stateful, durable, observable, evaluable, secure, and ready for production.

You’ll build your understanding step by step — starting with graphs, state, nodes, edges, and control flow, then progressing into tools, ReAct agents, persistence, durable execution, human-in-the-loop workflows, memory, subgraphs, and multi-agent architectures.

What You’ll Learn LangGraph environment setup and fundamentals Why graphs are useful for building agent workflows State, nodes, edges, and reducers Conditional routing and advanced control flow Tools and ReAct agent loops Checkpointers and conversation threads Durable execution and fault-tolerant workflows Human-in-the-loop agents Time travel and checkpoint-based debugging Long-term agent memory Subgraphs and modular agent architecture Supervisor-based multi-agent systems Swarm and agent handoff patterns Planning, execution, and reflection Streaming agent execution and events Agent observability and tracing Agent evaluation and testing Production deployment Agent security and cost optimization Production AI Agent Engineering

The goal of this course is not just to show you how to create an agent that works