The source is an excerpt from an IBM Technology YouTube video that dissects the fundamental components of an AI agent. This anatomy is broken down into three main stages: sensing, where the agent gathers information through inputs like text or physical sensors; thinking, which involves processing data using a knowledge base of facts and rules, policy information, and reasoning logic, often leveraging Large Language Models (LLMs); and finally, acting, where the agent executes decisions by generating output like text, executing control commands, or making reservations. The entire process is enhanced by a feedback loop for constant evaluation and improvement, which includes reinforcement learning with human feedback. The transcript uses the detailed example of an agent booking travel reservations to illustrate how these components interact to achieve a complex goal.