Building the Agentic Software Factory

Turn AI coding agents into a dependable, team-wide software factory using context engineering, AI-TDD, and harness design.

Key Features
• Build reliable AI development workflows using context engineering, AI-TDD, and harness engineering.
• Learn to apply practical frameworks, including AEMM, Elastic Loop, and Context Diseases.
• Build a software factory where AI workflows scale across whole teams

Book Description
AI coding agents can generate code in seconds, but without the right engineering practices, they can also introduce bugs, technical debt, and inconsistent code. This book teaches you how to build reliable AI-assisted development workflows that scale from individual projects to entire teams, regardless of which coding assistant or model you use.

Rather than treating AI as a black box, you'll learn how AI coding agents work, why they succeed or fail, and how to build systems that consistently produce better results. You'll explore practical methods such as context and harness engineering, along with reusable frameworks such as AEMM, Elastic Loop, and Context Diseases, which you can apply to any development workflow.

You'll also learn how to write better specifications, use AI-TDD to improve code quality, build development harnesses that guide AI agents, and choose the right level of autonomy for different tasks. The book also covers AI security, team adoption, and how to scale from individual AI-assisted development to a software factory where multiple AI workflows work together.

By the end of this book, you'll understand how to move beyond vibe coding and adopt a disciplined, practical approach to AI-driven software development.

What you will learn
• Distinguish between vibe coding and agentic engineering for reliable AI development
• Apply context engineering to improve AI output and reduce common failures
• Write clear specifications to guide AI agents and reduce hallucinations
• Implement AI-TDD workflows to improve code quality and reliability
• Build development harnesses with context, quality checks, and workflow guidance
• Calibrate AI autonomy using the AEMM maturity model and Elastic Loop framework
• Secure AI development workflows against prompt injection and context leakage

Who this book is for
This book is for mid-level and senior developers, tech leads, and engineering managers who want to use AI coding agents effectively without sacrificing software quality. Readers should know version control, testing, CI/CD, and at least one modern programming language. No AI or machine learning experience is required.