LangChain vs LangGraph - Which One Should You Use?

Learn to build AI agents from scratch in this comprehensive 25-minute tutorial that compares LangChain and LangGraph frameworks for developing intelligent chatbots and automated workflows. Start with LangChain fundamentals to understand the difference between traditional LLMs and AI agents, then explore core components for building chatbots with memory and retrieval-augmented generation (RAG) capabilities. Progress to LangGraph for creating complex, stateful workflows that can loop, branch, and adapt based on conditions, perfect for sophisticated applications like research assistants. Follow hands-on demonstrations building a customer service chatbot with LangChain and a research assistant using LangGraph's state management and conditional branching features. Discover when to use each framework through practical examples, understand the transition from traditional software to agentic software architecture, and explore StateGraph concepts for workflow orchestration. Master the key differences between both frameworks while building production-ready AI agents with Python, complete with interactive labs for practical implementation experience.