LangGraph Explained for Beginners

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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

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