Building Agentic and Multi-Agent Systems with LangGraph

This comprehensive tutorial spanning nearly 2 hours explores how to build advanced LLM applications using LangGraph for agentic and multi-agent systems. Learn the fundamental concepts of GenAI prototyping patterns including Prompt Engineering, RAG, Fine-Tuning, and Agents, with special focus on LangChain and LangGraph as industry-standard orchestration tools. Discover how to build context-aware, reasoning applications by implementing RAG with LangChain, creating agentic RAG applications with LangGraph, and developing sophisticated multi-agent workflows. The session breaks down all necessary concepts and code examples to understand and implement these systems from start to finish. Supplementary materials include slides and code resources available through provided links. Perfect for developers looking to leverage context, reasoning, and external tools in their LLM applications while implementing the Reasoning-Action (ReAct) pattern for more intelligent AI systems.