LangGraph Studio: Build and Debug AI Agent Workflows

AI agents are transforming how we automate complex tasks, but managing their logic can be challenging. LangGraph Studio provides a powerful environment to build, test, and refine these stateful workflows. In this text-based course, you will start with foundational AI concepts and move step-by-step through creating your first multi-actor agents. You will learn how to write the underlying code, manage application state, and leverage LangGraph Studio's capabilities to debug and deploy reliable AI workflows. What you will learn: • Understand the core concepts of agentic AI and stateful LLM applications • Configure LangGraph Studio to connect with your development environment • Design and write code for multi-actor workflows and state graphs • Implement modern retrieval-augmented generation (RAG) patterns within your agents • Debug complex agent interactions by analyzing state transitions and execution logs • Apply prompt engineering basics to improve the reliability of your agentic workflows • Prepare and package your agent architectures for production deployment The course begins by defining key terminology and the basic architecture of LLM agents before moving into practical application. From there, you will progress through written exercises and code snippets that demonstrate how to structure, test, and ship robust workflows. This course is designed for beginners with an interest in AI. No prior experience with agentic development is required. Start reading today to build your foundation in agentic AI.