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For AI coding agents, accurately specifying your intent is the whole ballgame! Spec-Driven Development: Engineering with intent teaches you how to close the gap between what you mean and what your agents actually build. In this practical, tool-agnostic playbook, author Hari Krishnan shows you how to make your intent clear through structured specifications and then make those specs the primary control surface for your projects, rather than the code itself.
This book is hands-on from the very beginning. You’ll follow a running URL shortener application that grows in ambition from chapter to chapter. As you explore the intent-first spec-driven development model, you’ll learn to adjust your process for differences in alignment, human and agentic collaboration, and evolving outcomes. As the project scales into microservices, multiple repositories, and cross-team coordination, you’ll see how intent-led development pays out with infrastructure, deployment, security, acceptance testing, and architectural governance.
Everything you’ll read and do is grounded in established software engineering fundamentals—extreme programming, legacy code refactoring, technical debt management—so you can connect new AI workflows to what you already know. You’ll see how to drive defect fixes through specifications rather than direct code edits, how to apply SDD to brownfield codebases with no existing specs, and how to construct an intent-harness that continually improves its own workflows from implementation feedback.
Hands-on exercises, including team-based collaboration through a shared GitHub repository, let you practice the workflows as they’d play out on a real engineering team. A companion code repository with full commit history lets you follow every step of the implementation rather than just seeing the finished result.
what's inside
Intent-driven development—from spec to deployment
Autonomous iteration workflows Ralph loopand other agentic techniques
Extend Spec-Kit and OpenSpec
Measure intent-harness health and spec quality with concrete metrics
Integrate SDD into existing planning, review, and delivery processes
about the reader
For mid-to-senior engineers and engineering leaders already shipping production code with AI coding agents like Claude Code, GitHub Copilot, or Codex CLI. Readers should be comfortable with context-window limitations, reviewing product requirements and acceptance criteria, and setting up CI pipelines.
about the author
Hari Krishnan is Founder and CEO of Polarizer Technologies, where he helps teams build AI-native products and adopt AI-augmented development practices at scale. He has over two decades of experience, including roles at ThoughtWorks, Citrix, and McAfee, working across industry verticals including finance, telecom, logistics, and retail. Hari has led enterprise-wide initiatives in architecture, developer experience, test automation, and AI adoption. He is the creator of Intent-Driven Dev, where he shares Spec-Driven Development and other context-engineering techniques to enable human–agent collaboration through effective intent articulation.
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