AI Agents: The Definitive Guide

Foreword

I am pleased to write this foreword for Nicole’s book. We are using this book as course material in our University of Oxford Agentic AI workflows course, and it’s incredibly gratifying to see this work finally out in the world.

The history of software is, in many ways, the history of abstraction. Each major shift in computing has introduced a new layer that changed not only what we could build, but how we thought about building it. From this perspective, agentic AI is just the latest profound abstraction in our industry.

With agentic AI, AI has moved beyond raw foundation models. By incorporating goal-driven behavior, reasoning, memory, evaluation, governance, and context, we are now able to automate entire end-to-end workflows across enterprises. Organizations are rapidly moving beyond simple demos to build production-grade systems. In other words, agentic AI has officially become an engineering problem.

This is why AI Agents: The Definitive Guide arrives at such an important moment. At an architectural level, builders grapple with a complex web of execution challenges:

• State and persistence: how should an agent maintain state across a long-running task?

• Memory architecture: how should memory be structured, indexed, and retrieved?

• Multi-agent collaboration: how do multiple specialized agents collaborate text here effectively?

• Holistic evaluation: how do we evaluate behavior that unfolds across dozens of autonomous decisions, rather than a single static response?

• Security ...