Welcome to the ultimate Agentic AI using LangGraph playlist! In this series, we’ll take you from the fundamentals of Agentic AI — understanding how it differs from generative AI and tool-augmented chatbots — all the way to building powerful, production-ready systems using LangGraph. You’ll learn core concepts like state management, prompt chaining, orchestrator-worker patterns, conditional edges, tool calling, and multi-agent setups. Along the way, we’ll explore advanced workflows including RAG, agentic RAG, memory, persistence, observability, and deployment strategies. Whether you're a beginner or looking to master Agentic AI frameworks, this playlist will equip you to design, build, and debug sophisticated AI agent systems with confidence!
Curated by: CampusX (28 videos)
This video shows you how to build conditional workflows using LangGraph—where the next step depends on specific outcomes or decisions. What’s covered: Designing workflows with branching logic Handling quality evaluation (QE) checks Using LLM outputs to guide different paths (e.g., review handling) Perfect if you want more control over how your AI workflows adapt to different scenarios. Code - https://github.com/campusx-official/langgraph-tutorials ============================ Did you like my teaching style? Check my affordable mentorship program at : https://learnwith.campusx.in DSMP FAQ: https://docs.google.com/document/d/1OsMe9jGHoZS67FH8TdIzcUaDWuu5RAbCbBKk2cNq6Dk/edit#heading=h.gvv0r2jo3vjw ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 E-mail us at support@campusx.in ⌚Time Stamps⌚ 00:00 - Recap 04:38 - Conditional Workflow / QE 24:20 - LLM - Review Handling