Agentic AI systems allow artificial intelligence to manage complex tasks through autonomous, multi-step operations, extending beyond simple response generation. This chapter lays the groundwork for understanding these systems, preparing you for the prompt engineering techniques covered later.

Here, you will:

• Define agentic workflows and recognize their distinguishing features.
• Identify the essential components of AI agents, such as LLMs, memory, and tools.
• Examine the role of prompt engineering in directing the behavior of these sophisticated agents.
• Compare the unique aspects of prompting AI agents with standard LLM interaction.

We will also cover common agent architectures, including examples like ReAct, and introduce methods for evaluating agent effectiveness. The chapter wraps up with a hands-on analysis of a basic agent performing a task.