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Full Description
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:
Step-by-step guides to using AI APIs, SDKs, AI-generated data, and synthetic users
Up-to-date explanations of how to build AI-powered chatbots and assistants, AI-driven content-enhancement services, code generation and software development tools, and AI search and recommendation utilities
How to improve your interface and UX design with AI features
Explorations of business and scaling considerations, including how to monetize AI features, how to optimize AI for both performance and cost, and case studies of successful products that incorporate GenAI
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.
Contents
Introduction xxvii
Part I Foundations of Generative AI 1
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
Part II Designing for a Better AI Experience 119
Chapter 6 Human-AI Interaction and UX Design 121
Chapter 7 Optimizing AI for Performance and Cost 141
Part III Integrating AI into Applications 165
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
Part IV Business Considerations 289
Chapter 12 Ethical Considerations and Pitfalls 291
Chapter 13 Monetizing AI Features 317
Chapter 14 Successful AI-Powered Products 345
Index 369
