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Spec-Driven Software Development with AI: Build Production-Ready Software with Requirements, Specs, Tests, and AI Coding Agents
AI coding agents can write code fast. But fast code is not the same as reliable, maintainable, production-ready software.
Spec-Driven Software Development with AI teaches you how to move beyond vague prompts and “vibe coding” by using a structured engineering workflow that turns software ideas into clear requirements, practical specifications, acceptance criteria, tests, task cards, context packs, reviewed code, and release-ready systems.
Instead of asking an AI coding agent to “just build it,” you will learn how to guide the agent with the same discipline professional teams use to control define the requirement, write the spec, design the system, create tests, break the work into small tasks, provide focused context, review the output, manage change, and prepare the release.
Through a complete self-contained project, you will build a production-minded task management API and web dashboard step by step. You will work with user accounts, authentication, validation, task creation, CRUD behavior, labels, filtering, due dates, tests, security guardrails, refactoring workflows, release checklists, and post-release feedback loops.
No GitHub repository is required. Every important template, prompt, checklist, command, code file, project structure, review workflow, and troubleshooting guide is included inside the book.
What you will learnYou will learn how
Turn product ideas into clear functional and non-functional requirements
Write AI-ready specifications that coding agents can actually follow
Convert specs into acceptance criteria, tests, and task cards
Build context packs that prevent AI agents from losing direction
Use AI coding agents safely without giving them uncontrolled freedom
Review AI-generated code against specs, tests, security, and maintainability
Debug “almost right” agent output with structured failure notes
Refactor messy AI-generated code without changing behavior
Add authentication, user-level rules, validation, and security guardrails
Manage spec drift, change requests, legacy code, and team workflows
Use multi-agent workflows without losing human control
Prepare release-ready software with quality gates, release notes, and evidence
What you will buildInside the book, you will build a complete task management project that
A FastAPI-based backend API
SQLite database persistence
User registration and login
User ownership and authorization rules
Task creation, update, completion, reopening, deletion, labels, filtering, and due dates
A minimal web dashboard
Unit, integration, validation, security, and regression tests
Agent instruction files, task cards, context packs, project memory notes, and release documents
A capstone feature package that takes a real feature from request to production-ready release
Who this book is forThis book is for developers, beginner programmers, freelancers, startup builders, QA engineers, tech leads, and software professionals who want to use AI coding agents seriously.
If you have ever generated code with AI and then struggled with unclear requirements, missing tests, messy structure, hidden assumptions, broken behavior, or difficult reviews, this book gives you a practical workflow for staying in control.
You do not need to be an expert software architect to benefit from this book. The explanations are step by step, the project is self-contained, and the workflow is designed to be useful for both beginners and experienced professionals.
Why this book is differentMost AI coding guides focus on better prompts.
This book goes further.
Spec-Driven Software Development with AI teaches you how to move beyond vague prompts and “vibe coding” by using a structured engineering workflow that turns software ideas into clear requirements, practical specifications, acceptance criteria, tests, task cards, context packs, reviewed code, and release-ready systems.
Instead of asking an AI coding agent to “just build it,” you will learn how to guide the agent with the same discipline professional teams use to control define the requirement, write the spec, design the system, create tests, break the work into small tasks, provide focused context, review the output, manage change, and prepare the release.
Through a complete self-contained project, you will build a production-minded task management API and web dashboard step by step. You will work with user accounts, authentication, validation, task creation, CRUD behavior, labels, filtering, due dates, tests, security guardrails, refactoring workflows, release checklists, and post-release feedback loops.
No GitHub repository is required. Every important template, prompt, checklist, command, code file, project structure, review workflow, and troubleshooting guide is included inside the book.
What you will learnYou will learn how
Turn product ideas into clear functional and non-functional requirements
Write AI-ready specifications that coding agents can actually follow
Convert specs into acceptance criteria, tests, and task cards
Build context packs that prevent AI agents from losing direction
Use AI coding agents safely without giving them uncontrolled freedom
Review AI-generated code against specs, tests, security, and maintainability
Debug “almost right” agent output with structured failure notes
Refactor messy AI-generated code without changing behavior
Add authentication, user-level rules, validation, and security guardrails
Manage spec drift, change requests, legacy code, and team workflows
Use multi-agent workflows without losing human control
Prepare release-ready software with quality gates, release notes, and evidence
What you will buildInside the book, you will build a complete task management project that
A FastAPI-based backend API
SQLite database persistence
User registration and login
User ownership and authorization rules
Task creation, update, completion, reopening, deletion, labels, filtering, and due dates
A minimal web dashboard
Unit, integration, validation, security, and regression tests
Agent instruction files, task cards, context packs, project memory notes, and release documents
A capstone feature package that takes a real feature from request to production-ready release
Who this book is forThis book is for developers, beginner programmers, freelancers, startup builders, QA engineers, tech leads, and software professionals who want to use AI coding agents seriously.
If you have ever generated code with AI and then struggled with unclear requirements, missing tests, messy structure, hidden assumptions, broken behavior, or difficult reviews, this book gives you a practical workflow for staying in control.
You do not need to be an expert software architect to benefit from this book. The explanations are step by step, the project is self-contained, and the workflow is designed to be useful for both beginners and experienced professionals.
Why this book is differentMost AI coding guides focus on better prompts.
This book goes further.
609 pages, Kindle Edition
Published July 11, 2026
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