Analyze the Anatomy of an AI Agent¶
| Course | Hands-on Agentic AI for Leaders |
| Session | Session 5: Autonomous Agents & ChatGPT Agent |
| Module | Analyze and Design Agent Architectures |
| Type | Live |
Analyze the core components every AI agent shares—LLM brain, tools, memory, instructions, and knowledge—then distinguish agents from structured workflows on the agentic systems spectrum to determine when autonomous agents are the right solution for a business problem.
Objectives¶
- Distinguish between agents and workflows by comparing their autonomy levels, decision-making capabilities, and appropriate use cases on the agentic systems spectrum
- Identify the core components of an agent (LLM brain, tools, memory, instructions, knowledge) and explain how these components work together regardless of platform
- Evaluate business scenarios to determine when autonomous agents are appropriate versus structured workflows, based on task predictability, complexity, and need for dynamic planning
- Select optimal use cases for agentic implementation by matching task characteristics (open-ended problems, multi-step complexity, tool requirements) to agent capabilities