In this video, I break down what AI agents actually are (without the hype) and how they work end-to-end when you build them from scratch. I explain an agent as a system that can perceive what’s happening, reason about it, and then take actions—looping through a practical “sense → plan → act” cycle. I also walk through the six core building blocks I use when I design agentic systems: perception, reasoning, action, a knowledge base, learning, and communication. If you’ve been confused between “LLM chatbot” vs “agent,” this is the mental model that clears it up. Then I go one layer deeper into architecture: the orchestration layer (the control center that triggers and manages the loop), the models layer (where patterns like ReAct, Chain-of-Thought, and Tree-of-Thoughts help the agent think), and the tools layer (where the agent interacts with the real world via APIs, code, search, and more). Finally, I show how a query flows through an AI agent and why design patterns matter if you want reliable behavior in production—not just demos. You’ll leave knowing where agents fit, how they’re structured, and what to build next if you want real agent projects.