What if you could build intelligent applications that think, write, reason, and adapt-using nothing but Python and modern AI models?
This book shows you exactly how to do it.
Generative AI with Python is a practical, hands-on guide to designing, building, securing, and deploying real-world generative AI applications using large language models. Rather than drowning you in theory, this book focuses on how generative AI actually works in production-how prompts behave, why models fail, where costs explode, and how to build systems that are reliable, secure, and scalable. You'll move from core concepts to advanced topics such as retrieval-augmented generation, performance optimization, security risks, ethical considerations, and responsible deployment-without losing clarity or momentum.
By reading this book, you will:
Understand how large language models process tokens, prompts, and context
Design effective prompts and reusable prompt patterns
Build efficient, cost-aware AI applications in Python
Secure your systems against prompt injection and data leakage
Optimize performance using caching, reuse, and monitoring strategies
Deploy generative AI responsibly, with fairness, transparency, and safety in mind
What makes this book different is its developer-first mindset. It bridges the gap between experimentation and production, combining practical engineering guidance with real-world architectural insight. Instead of isolated examples, you learn how the pieces fit together-code, prompts, infrastructure, security, and ethics-so you can confidently ship AI-powered systems that last.
If you're a Python developer, software engineer, or technical professional who wants to move beyond hype and actually build with generative AI, this book was written for you.
Start building smarter applications today-turn Python into your gateway to the future of intelligent software.
