The argument
Enterprises build lasting advantage not by accumulating technologies, but by converting specialized expertise into organizational capability that outlives the person, project, or platform that created it.
Every new technology promises to make your organization faster. Most organizations end up slower: more systems, more handoffs, and more of what matters locked in the heads of a few people. The enterprises that pull ahead are rarely the first to adopt. They are the ones that know how to turn what their best people know into something the whole organization can use, and keep using after those people move on.
This book shows how they do it. Across 27 chapters, real cases from Amazon's API mandate to Air Canada's chatbot ruling show what works and what fails, and each chapter gives you a mechanism to put it to work: the decision to make, the steps for making it, and the measures that tell you whether it is working. It also takes on the question every leader now faces: when AI can write working software for anyone who asks, what still sets your organization apart?
Five parts, 27 chapters
The book is written for chief information officers, chief technology officers, and chief digital officers, and the directors and architects who work with them. It is also for the executives and board members who fund technology and answer for it, and for anyone who wants to know why some organizations grow more capable with every new technology while others start over each time.
Its five parts build on one another, from how enterprises evolve to what it means to lead a technology organization for the long term.
Part I: Evolve
Why complexity follows success, and how architecture and business capabilities keep decisions coherent.
Part II: Design
Strategy, operating models, platforms, cloud, security, data, and AI engineering.
Part III: Deliver
Shipping safely and repeatedly, from DevSecOps and the software supply chain to observability and SRE.
Part IV: Govern
Who decides, how much risk the enterprise carries, and how AI is held to account.
Part V: Steward
What the technology organization is for when almost anyone can build, and what it means to lead it for the long term.
See all 27 chapters
Part I: Evolve
- Why Technology Organizations Struggle to Scale
- The Economics of Software
- The Evolution of Enterprise Technology
- Enterprise Architecture: Designing Organizations That Scale
- Business Capabilities: The Stable Foundation of the Enterprise
Part II: Design
- Business Strategy, Technology Strategy, and Capability Investment
- Operating Models: Organizing the Enterprise for Continuous Value Delivery
- Designing the Modern Technology Organization
- Technology Operating Models: Coordinating Enterprise Capability Providers
- Platform Engineering: Packaging Expertise into Reusable Organizational Capability
- Internal Developer Platforms: Delivering Platform Engineering at Scale
- Cloud Engineering: Building Infrastructure as Organizational Capability
- Security Engineering: Building Trust as an Enterprise Capability
- Data Engineering: Making Information an Enterprise Capability
- AI Engineering: Making Intelligence an Enterprise Capability
Part III: Deliver
- Modern Software Delivery: The Enterprise Value Stream
- DevSecOps: Running Security Inside the Delivery Stream
- The Software Supply Chain: Trusting What Teams Build From
- GitOps: Keeping Running Systems True to What Was Declared
- Continuous Delivery: Changing Software in Small, Safe Steps
- Observability: Seeing What Running Systems Are Doing
- Site Reliability Engineering: Keeping Services as Reliable as the Business Needs
Part IV: Govern
- Governance: Deciding Who Decides
- Enterprise Risk: Knowing How Much Risk the Enterprise Is Carrying
- AI Governance: Answering for What AI Systems Do
Part V: Steward
- When Anyone Can Build Software: What the Technology Organization Is For
- Executive Stewardship: Leaving the Enterprise More Capable Than You Found It
How every chapter works
- A real, named caseThe idea at work in an actual enterprise, with sources cited.
- A contrasting caseWhere the idea failed, showing what success depended on.
- A mechanism you can useThe decision it governs, the steps for making it, and the measures that tell you whether it is working.
- A path for late startersHow an organization that is behind can begin.
- Where This Breaks DownThe conditions under which the argument stops applying.
Some of the cases
Each chapter is built on cases from the public record, cited chapter by chapter.
- Amazon's API mandate
- Spotify's Backstage and Golden Paths
- ING's squads and tribes
- Google's error budgets
- The Equifax breach
- Zillow Offers
- CrowdStrike's Channel File 291
- Air Canada's chatbot ruling
- Morgan Stanley's AI assistant
- Etsy's deploys
- Target's breach
- Walmart's replaceable providers