LangChain Deep Agents Tutorial for Beginners | Build Your First DB Agent with LangGraph & LangSmith

Description

In this tutorial, we build our first Deep Agent using LangChain’s Deep Agent framework and understand how Deep Agents work internally. This is a beginner-friendly hands-on tutorial where we create a simple DB Agent (Hello World style) using LangChain, tools, and OpenAI models. In this video, you will learn: ✅ How to set up a Deep Agent project using UV ✅ Installing LangChain Deep Agents dependencies ✅ Creating your first tool in LangChain ✅ Building a Deep Agent with create_deep_agent() ✅ Invoking the agent with user messages ✅ Understanding tool execution flow ✅ Debugging Deep Agents using LangSmith ✅ Exploring built-in middleware (Todo, Summarization, Sub-agent middleware) ✅ Understanding how Deep Agents create execution plans automatically We also inspect the internal Deep Agent architecture and understand how middleware orchestration works behind the scenes. This tutorial is perfect for: AI Engineers LangChain Developers Agentic AI Developers LLM Application Developers Beginners learning AI Agents Tech Stack Used: LangChain Deep Agents OpenAI GPT Models Visual Studio Code LangGraph LangSmith Python 3.12 UV Package Manager GitHub code will be shared in the repository. If you are learning Agentic AI, Multi-Agent Systems, LangChain, or LangGraph, this series will help you build production-ready AI agents. 👍 Like the video if you found it useful 🔔 Subscribe for more AI Engineering tutorials #LangChain #DeepAgents #LangGraph #LangSmith #AIAgents #AgenticAI #OpenAI #PythonTutorial