Introduction - Architecting Autonomous Systems
Introduction
These lesson notes are designed to introduce the following concepts
Mechanics of Agency & Intelligence
Anatomy of AI agents
AI agent terminology
Objectives
Gain a basic overview of concepts associated with the mechanics of agency and intelligence
Understand the anatomy of AI agents (what AI agents are and their main components)
Understand the anatomy of AI agents (what AI agents are and what their main components are)
Explore code-bases (Python based AI agent examples)
Here, learners will gain knowledge to help them interpret the concepts, processes, and components that make AI agents work.
Prerequisites
Prerequisites
Basic understanding of LLMs (see Building Blocks of GPT-2 LLM)
Python programming
Lesson notes (content)
Fundamentals of Autonomous Systems
Tools, Interoperability, and the Model Context Protocol (MCP)
Context Engineering for Stateful AI Agents; Sessions, Persistent Memory and context injection
Explore Python code snippets demonstrating a range of concepts
Case study part 1: Explore Anatomy and Taxonomy of Agents
Case study part 2: Explore basics of context engineering
Engineering Trust
Target audience
These lesson notes are for individuals who need to explore fundamental concepts associated with AI agents. These notes are not designed to demonstrate how to develop and deploy production-ready AI agents.
Credits
GitHub pages are built using the CodeRefinery Sphinx lesson template
Figures are generated using the Google NotebookLM (NotebookLM slides)