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In Lecture 25 of the Gen AI Series, we dive deep into one of the most important foundations of Agentic AI development — LangGraph Workflows. This class focuses on how state, nodes, edges, conditional routing, and workflow design come together to build powerful, controllable AI systems. This lecture is a complete, step-by-step walkthrough starting from the basics of state containers, creating nodes as functions, defining edges, and designing multiple workflow patterns used in modern agentic AI. 🔥 What You Will Learn in Lecture 25 ✔️ What is State in LangGraph ✔️ State as a shared memory container ✔️ Using TypedDict / Pydantic to create schema ✔️ How nodes are created as functions ✔️ Node input/output mechanism ✔️ How state is updated partially or fully ✔️ What nodes can and cannot modify ✔️ Creating different types of Workflows: Sequential Workflow Parallel Workflow Mixed (Sequential + Parallel) Workflow Conditional Workflow (with dotted edges) ✔️ Understanding conditional edges and routing logic ✔️ Role of Start and End nodes ✔️ How LangGraph compiles and visualizes workflows ✔️ When and why workflows are used in Agentic AI ✔️ How LangGraph compares to frameworks like CrewAI, AutoGen, N8N, ADK ✔️ Why LangGraph is more powerful for real production-grade agent systems 📌 Highlights from the Practical Demo Creating a state schema (PersonalInfo, RoutingState) Writing node functions (nodeA, nodeB, categorize, handle_math, etc.) Updating state inside nodes Adding nodes to the graph Connecting nodes with edges Implementing conditional routing using: builder.add_conditional_edges( "categorize", route_question, { "math": "math_handler", "science": "science_handler", "general": "general_handler" } ) Visualizing the final workflow Running examples like: “What is Newton’s third law?” → routed to Science Handler 📚 Who Should Watch This Lecture? This lecture is perfect for: AI/ML engineers Students learning GenAI workflow design Developers building Agentic AI, RAG systems, or multi-step reasoning pipelines Anyone preparing for interviews on LangChain, LangGraph, CrewAI, Autonomous Agents, etc.