LangChain + LangGraph Tutorial: Build AI Agents (Free Labs)

🧪Try LangChain Labs for Free: https://kode.wiki/462mo31
🧪Try LangGraph Labs for Free - https://kode.wiki/41WTH62

Master AI agent development from scratch with this beginner-friendly LangChain and LangGraph tutorial. Build your first intelligent chatbot with memory, retrieval, and workflow automation using Python.

In this video you'll master both LangChain and LangGraph, understanding exactly when to use each framework. We start with LangChain fundamentals for building chatbots with memory and RAG, then level up to LangGraph for complex, stateful workflows like research assistants that can loop, branch, and adapt based on conditions.

🎓 Perfect for Beginners - No AI Experience Required

⏰ Video Timeline:
00:00 - Why you need LangChain
00:58 - LLMs vs AI Agents Explained
02:05 - Traditional Software vs Agentic Software
02:29 - LangChain Core Components
03:36 - Traditional Software vs Agentic Software
04:47 - Practical Lab Demo Introduction
05:20 - Demo - LangChain
12:03 - Introduction to LangGraph
12:23 - LangChain vs LangGraph: What’s the real difference?
13:22 - Deep Research Assistant Use Case Example
13:56 - Traditional approach pain points
14:24 - Orchestration in LangGraph
15:11 - What is StateGraph?
15:42 - LangGraph Workflow
16:45 - LangGraph Adoption in Business Requirements
17:19 - Demo - LangGraph
24:55 - Conclusion & Free Lab Access

🚀 Hands-On Labs Included:
Follow along with our free interactive labs covering everything from installation to deploying production-ready AI agents. Build a customer service chatbot with LangChain, then create a sophisticated research assistant using LangGraph's state management and conditional branching.

🧪Try LangChain Labs for Free: https://kode.wiki/462mo31
🧪Try LangGraph Labs for Free - https://kode.wiki/41WTH62


🔔 SUBSCRIBE for cutting-edge AI tutorials that actually matter!


#LangChain #LangGraph #Chatbot #AIAgent #LearnAI #Coding #python #kodekloud