Buch, Englisch, 208 Seiten, Format (B × H): 185 mm x 231 mm, Gewicht: 295 g
How to Build Systems That Drive Product Success in an Ai-Driven World
Buch, Englisch, 208 Seiten, Format (B × H): 185 mm x 231 mm, Gewicht: 295 g
ISBN: 978-1-394-37846-3
Verlag: Wiley
Build software that users actually use with proven growth-oriented software development strategies
In Growth Engineering: How to Build Systems That Drive Product Success in an AI-Driven World, experienced software engineer with the Microsoft Experiences + Devices Growth team, Rita Okonkwo, delivers a strategic guide for anyone interested in building tech products that scale organically through smart technical choices.
You'll learn how clean architecture, thoughtful instrumentation, and experimentation frameworks directly influence growth outcomes. With a focus on practical systems and real-world decision-making, this book shows how to build software that gains traction, drives engagement, and supports continuous iteration.
You'll learn all about key growth engineering strategies like feature flighting, data-driven experimentation, logging, and metrics tracking. You'll find real-world case studies that break down design systems that support rapid iteration, and data-based product decision-making.
Inside the book: - Why growth engineering matters and how engineers can get directly involved in it
- Experimentation strategies, including controlled rollouts and effective A/B testing techniques
- How to build scalable data pipelines and integrate real-time analytics
- Ways to create a growth-first engineering culture, generating faster iterations without sacrificing quality
Perfect for software engineers, product managers, and developers interested in building products that users love, Growth Engineering: How to Build Systems That Drive Product Success in an AI-Driven World is a must-read for entrepreneurs, founders, and other technology business leaders ready to discover how to consistently create commercially successful software.
Autoren/Hrsg.
Weitere Infos & Material
Preface xv
Foreword xvii
Introduction xxi
Chapter 1 Growth Engineering 1
Chapter 2 Observability 7
Chapter 3 Data Pipelines 29
Chapter 4 Data Modeling 55
Chapter 5 What Are Experiments? 83
Chapter 6 Types of Product Experiments 99
Chapter 7 Introduction to A/B Testing 115
Chapter 8 Building a Growth Engineering Team 133
Chapter 9 The Future of Growth Engineering 149
Chapter 10 The Growth Engineer's Workflow 165
Key Questions for Reflection 177
Exercises 178
Index 179
