
Agentic AI Chapter 2: The Agent Loop
How an agent actually works: the LLM decides, the runtime validates and executes, and the loop repeats until the goal is met. Walked through turn by turn with the iPhone 18 launch-day example.
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How an agent actually works: the LLM decides, the runtime validates and executes, and the loop repeats until the goal is met. Walked through turn by turn with the iPhone 18 launch-day example.

The model never runs a tool. It only asks for one in a structured format, and the runtime validates and executes it. Explained with the iPhone 18 launch-day example.

Before building an agent, ask whether you need one. A workflow follows fixed steps. An agent decides what to do next. Explained with an Amazon returns example.

A comprehensive guide to Retrieval-Augmented Generation for beginners. Learn how RAG solves LLM limitations, why fine-tuning falls short, and how to build systems that ground AI responses in real data.

Agentic AI: From Reactive Chatbots to Proactive Agents That Reason, Plan, and Act

Basics of generative AI