The course aims to explain Large Language Models (LLMs), AI Workflows, and AI Agents, moving from simple concepts to more complex, autonomous systems. It begins by establishing that LLMs, such as ChatGPT, are passive and lack proprietary knowledge, which limits their utility. The lesson then introduces AI Workflows as a human-defined series of steps for an LLM to follow, often involving external tools for data retrieval—with Retrieval Augmented Generation (RAG) noted as a key example. Finally, the course explains the culmination with AI Agents, which are defined by the critical replacement of the human decision-maker with an LLM that can reason, act using tools, and autonomously iterate to achieve a set goal, often structured using the ReAct framework.
