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Currently Playing: LangGraph Core Concepts | Agentic AI using LangGraph | Video 4 | CampusX

This video breaks down the key building blocks of LangGraph. You’ll learn how to design and manage LLM workflows using concepts like prompt chaining, routing, parallel execution, and graph-based orchestration. We cover: How LangGraph structures workflows with nodes and edges How state, reducers, and orchestrators work together The full execution model that powers agentic AI systems ============================ 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 Slide into our DMs: 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 - Intro 01:14 - What is LangGraph? 05:43 - LLM WorkFlows 09:07 - Prompt Chaining 11:17 - Routing 13:14 - Parallelization 16:11 - Orchestrator Workers 19:48 - Evaluator Optimizer 23:00 - Graphs Nodes and Edges 30:53 - State 36:07 - Reducers 44:38 - LangGraph Execution Model


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