LangGraph Memory Management Explained 🔥 | Tracing with LangSmith (Part 3)

Welcome to Part 3 of my LangGraph series! 🚀 In this video, we explore one of the most important topics in building real-world AI agents: 🔹 Memory Management in LangGraph 🔹 Tracing and Debugging with LangSmith 📦 Resources & Links: Code: https://github.com/Sandesh-hase/Langgraph-Tutorial.git LangGraph Tutorial: https://www.youtube.com/playlist?list=PLLPrkPALrjwtrIwOgtEq9cBPMF3Svae_G Agentic RAG-Part-1: https://youtu.be/MDbKg9q_UJk Agentic RAG-Part-2: https://youtu.be/LhlT5xwt-pQ Agent Foundry Mastery: https://youtu.be/-gaFEfFJYLc?si=Kp9z8m2ISz6fo6vc Autogen Playlist: https://www.youtube.com/playlist?list=PLLPrkPALrjwthstGWapGz9NRuy6p8cVTX Azure AI Foundry:Prompt Flow, Finetuning GPT4-o, RAG, LLMOps : https://www.udemy.com/course/develop-generative-ai-apps-in-azure-ai-foundry/?referralCode=33D87106042F2F66083D Agentic AI Developemnt with Azure & Semantic Kernel Course: https://www.udemy.com/course/agentic-ai-development-with-azure-semantic-kernel/?referralCode=9528210DF4484E6A4810 MCP: https://youtu.be/iqya5VRRJj0?si=UHA9tIbnZNFE2lcT If you’ve ever wondered how AI assistants remember conversations, manage context, and stay efficient, this session is for you. We break it down into three parts with hands-on examples using a Travel Assistant: 1️⃣ Without Memory – A stateless travel agent that can’t recall previous messages. 2️⃣ With Memory – Adding conversation memory so the agent remembers past queries. 3️⃣ Summarized Memory – Smart memory compression for handling long conversations without overwhelming your LLM. ✅ Tracing with LangSmith – Debug, monitor, and visualize your LangGraph runs Finally, we integrate with LangSmith, which helps you: ✨ Visualize and trace your agent’s reasoning. ✨ Debug and optimize memory usage. ✨ Gain insights into performance and costs. By the end of this video, you’ll have the tools to: ✅ Design scalable AI assistants with effective memory strategies. ✅ Avoid costly mistakes when managing context windows. ✅ Leverage LangSmith for debugging, tracing, and optimization. 🔔 Make sure to subscribe so you don’t miss the next videos in this series where we’ll continue exploring LangGraph’s advanced features! 💬 Drop your questions in the comments — I’ll be happy to discuss and help you build your own LangGraph projects. #LangGraph #LangSmith #AIagents #GenerativeAI #LangChain #LLM #AIWorkflows #MemoryManagement #ConversationalAI #OpenAI #ArtificialIntelligence #AICommunity #MachineLearning #DeepLearning