AI Agent Fundamentals

Large Language Models (LLMs) and Generative AI have unlocked many valuable use cases, such as content creation and document summarization. For more complex applications like workflow automation, coding assistance, and advanced customer support chatbots, we need a way for LLMs to make decisions and trigger real-world actions: enter AI agents! In this skill track, you'll learn what AI agents are and what they can (and can't!) be used for through real-world examples. You'll discover practical frameworks like the Thought-Action-Observation (TAO) loop and ReAct prompting to better conceptualize how AI agents make decisions. You'll find out what makes an AI agent successful in production, and why so many fail to get out of development. You'll learn the latest practices for building scalable agentic systems, like emerging multi-agent design patterns, the Model Context Protocol (MCP), and the Agent-to-Agent (A2A) protocol. Discover how AI agents can begin changing the way you work today!