Tina Huang offers a beginner-friendly guide to building AI agents using both no-code and code-based tools. She explains agents as systems that perceive, reason, and act, often mimicking roles like customer support or coding assistants. The course introduces a modular framework—covering models, tools, memory, audio, guardrails, and orchestration—alongside workflows like prompt chaining, routing, and autonomous agents. Real-world examples include a refund bot, news aggregator, and financial research assistant. You’ll also learn a prompt-engineering framework and how to choose agent ideas by identifying workflow pain points, focusing on simplicity and real-world usefulness over unnecessary complexity.