LangGraph + Neo4j Crash Course for Beginners: AI Agent Development using Knowldege Graph | Hands-on! - Context Engineering for AI Agents Using LangGraph: Semantic Memory | Step-by-Step

*Resources:* - GitHub: https://github.com/homayounsrp/MCP-Powered-Memory-for-Agent - The credit for this knowledge goes to this course: https://learn.deeplearning.ai/courses/long-term-agentic-memory-with-langgraph/lesson/ovv0p/introduction *Previous Videos:* - Part 2: Building an AI Agent with LangGraph & Neo4j: https://youtu.be/2oFg4rTT-UY?si=fDEg6geTorsC9lCp - Part 4: Building a Supervised Agentic RAG : https://youtu.be/qcYWzVIuMTk?si=wLihZUhdtjniJGlE - Part 8: Building an Online Learning AI Agent | Non-Technical Explanation: https://www.youtube.com/watch?v=LmVDUChGvXw&t=71s In this video, I walk you through real-world context engineering for AI agents using Model Context Protocol (MCP), LangGraph, and a fully implemented semantic memory system. Context engineering is the practice of designing how an AI agent manages information across tools, steps, and sessions. It’s what transforms an LLM from a reactive chatbot into a proactive assistant—one that remembers, adapts, and evolves over time. We start by using MCP as the backbone for structured agent context, ensuring that goals, inputs, outputs, and intermediate states are preserved and shared across multiple components. Then, with LangGraph, we orchestrate multi-step, stateful workflows. Finally, I show you how to implement LangMem’s semantic memory—allowing the agent to persist and retrieve key knowledge from past interactions. This isn’t just theory—you’ll see a working demo of a context-aware agent that retains meaning, recalls user-specific details, and makes smarter, more relevant decisions over time. If you’re serious about building AI systems that scale and actually understand users, then context engineering is the skill to master. And this video will show you how to start doing it, step by step. ----- Timestamps: 0:00 - Intro 1:00 - System Design 2:53 - Implementation 12:44 - Demo 14:38 - Outro LangGraph,MCP,Model Context Protocol,LangGraph tutorial,build AI agent,LangGraph MCP integration,AI agents,LangGraph agents,MCP integration,Using MCP with LangGraph agents,Context Engineering for Agents,Context Engineering — The Hottest Skill in AI Right Now,Context Engineering is the New Vibe Coding (Learn this Now),Context Engineering vs. Prompt Engineering: Guiding LLM Agents,Context Engineering: What It Is and Why It Matters