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Enterprise AI Software Engineering
Paperback
Publisher: Independently Published
Published: Aug 6 2026
Pages: 126
Weight: 0.51
Height: 0.27 Width: 7.00 Depth: 10.00
Language: English
If AI can write the code, why are enterprise software projects still so expensive?
I've been asked that question by CEOs reviewing budgets, by customers who just watched an AI build a working app in twenty minutes, and by architects arguing with me over coffee. My answer is always the same: writing code was never the expensive part of enterprise software. And AI hasn't changed that. It's changed something else entirely.
After twenty years designing and delivering enterprise systems, incentive compensation platforms, BI modernizations, data migrations that touched every corner of a company, I've watched AI redistribute engineering effort rather than eliminate it. The typing gets faster. The judgment gets more valuable. That shift is the reason this book exists.
Enterprise AI Software Engineering introduces the EASE Framework: Explore, Architect, Scale with AI, Evolve. It's not another delivery methodology competing with Agile or Scrum. It's a decision framework that answers one question at every stage of a project: where should humans lead, and where should AI accelerate?
Inside, you'll find:
- Why the AI should cut costs 80% assumption is wrong, and what actually drives enterprise software cost
- A four-stage framework for AI-assisted delivery, built from real project estimates, not theory
- The eight factors that separate a $450K project from a $1.8M one, with a full worked example
- How architecture becomes more valuable, not less, as code generation gets cheap
- Field-tested lessons from banking compensation platforms, BI migrations, and enterprise data cleanups
- How to lead engineering teams through the AI transition without losing your next generation of senior talent
This book is for two audiences who usually read different books and argue with each other in the same steering committee meetings: the architects, CTOs, and senior engineers building AI-assisted systems, and the CEOs, CFOs, and product leaders funding them.
If you've ever had to explain why software still costs what it costs, or wondered whether your engineering judgment still matters in an AI-saturated industry, this book gives you the framework and the language to answer both questions with confidence.
Not another AI hype book. Not a prompt engineering guide. A practitioner's framework for building software that still works three years from now.
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