LangGraph Explained for Beginners

🧪Try LangGraph Hands-On Labs for Free - https://kode.wiki/41WTH62 Learn how LangGraph transforms simple LangChain chatbots into powerful AI agents with StateGraph, loops, and conditional workflows! In this comprehensive video, we'll show you exactly how to build a production-ready AI Research Assistant that searches the web, evaluates trustworthiness, extracts facts, and generates intelligent reports using nodes, edges, and shared state management. Ready to build your own stateful AI workflows? Access our FREE interactive labs where you can experiment with real LangGraph implementations, create your own StateGraph architectures, and see agentic AI workflows in action! 🧪Try LangGraph Hands-On Labs for Free - https://kode.wiki/41WTH62 📚 What You'll Learn: • LangChain vs LangGraph: When to use each framework • How StateGraph works with nodes, edges, and persistent memory • State management patterns for production AI agents • LangGraph Workflow Demo ⏱️ Timestamps: 00:00 - Introduction to LangGraph 00:20 - LangChain vs LangGraph: What’s the real difference? 01:19 - Deep Research Assistant Use Case Example 01:53 - Traditional approach pain points 02:21 - Orchestration in LangGraph 03:08 - What is StateGraph? 03:39 - LangGraph Workflow 04:42 - LangGraph Adoption in Business Requirements 05:16 - Demo - Installing LangGraph Ecosystem 05:50 - Demo - Sequential Workflow vs Stateful Workflow 06:29 - Demo - Chunking Strategy and Embedding 07:37 - Demo - StateGraph 08:29 - Demo - Nodes, Edges and Routing 09:38 - Demo - Loops and Iterations 10:15 - Demo - Tool Integration 10:45 - Demo - Memory and State 11:27 - Demo - Build Your Own Research Assistant 12:52 - Conclusion & Free Lab Access 🔔 Subscribe for more AI tutorials! #LangGraph #LangChain #StateGraph #AIagents #AgenticAI #AIworkflows #AIautomation #LLM #OpenAI #Python #AutonomousAgents #workflowautomation #kodekloud