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A Developer's Guide to Integrating Generative AI into Applications
Chris Minnick (Author)
9781394373130, Wiley
Paperback / softback, published 16 February 2026
416 pages
23.1 x 18.5 x 2 cm, 0.794 kg
Create, implement, and scale commercially successful generative AI applications that solve real-world problems In A Developer's Guide to Integrating Generative AI into Applications, software developer, technology educator, and author Chris Minnick explain exactly how to design and implement scalable generative AI applications. The book walks you through building production-ready GenAI applications, covering the key architectural choices, integration patterns, and design practices needed to deliver accurate, efficient, and commercially viable solutions. Minnick demonstrates the principles and techniques you need to succeed in the rapidly evolving GenAI space in real-world business environments. He shows how to overcome the practical challenges developers face when embedding generative AI into products, from designing effective prompts to managing performance and cost, with hands-on examples that demonstrate proven techniques you can apply immediately. You’ll discover: Perfect for software developers, product managers, engineering leaders, and UX designers, A Developer's Guide to Integrating Generative AI into Applications is your essential guide to integrating generative AI into real products and creating the AI-powered applications that will define the next era of software.
Introduction xxvii Part I Foundations of Generative AI 1 Part II Designing for a Better AI Experience 119 Part III Integrating AI into Applications 165 Part IV Business Considerations 289 Index 369
Chapter 1 Introduction to Generative AI 3
Chapter2 Understanding Generative AI Models 25
Chapter 3 Getting Started with AI APIs and SDKs 47
Chapter 4 AI-Generated Data and Synthetic Users 75
Chapter 5 Prompt Engineering 91
Chapter 6 Human–AI Interaction and UX Design 121
Chapter 7 Optimizing AI for Performance and Cost 141
Chapter 8 Building AI-Powered Chatbots and Assistants 167
Chapter 9 Generating and Enhancing Content with AI 205
Chapter 10 AI for Code Generation and Developer Tools 239
Chapter 11 Enhancing Search and Recommendations with AI 263
Chapter 12 Ethical Considerations and Pitfalls 291
Chapter 13 Monetizing AI Features 317
Chapter 14 Successful AI-Powered Products 345
Subject Areas: Computer science [UY]
