Books

ChatGPT can save you time, sharpen your ideas and change the way you work, but only if you know how to use it well. This practical guide takes you from your first prompt to advanced techniques, with real-world examples for writing, research, coding, business and creativity. Learn what works, what doesn’t and how to get better results every day.

Build smarter AI applications with Redis at the core. This practical guide shows you how to use vector search, RAG, semantic caching, agent memory and real-time inference to create fast, scalable systems. With runnable Python examples throughout, you’ll learn how to take AI projects from prototype to production.

Unlock the full potential of Qwen 3.8 with a practical guide built for real results. Learn the techniques behind stronger prompts, avoid common mistakes, and create reliable outputs for coding, research, business, creative projects and AI agents with clear examples you can use right away.

Build MCP servers that are ready for real production. This hands on guide shows you how to design, secure, deploy and operate stateless Model Context Protocol servers that scale with confidence. Packed with practical examples and proven patterns, it gives you the skills to build reliable AI infrastructure from the ground up.

The Python AI ecosystem has hundreds of excellent libraries that nobody writes about because LangChain dominates the conversation. This book covers 38 of them. Each chapter is a practical guide: what the library does, why it exists, how to install it, and working Python code you can run today. No fluff, no theory — just tools and code.

AI changes the security game. New attack paths demand new ways of thinking. This practical guide shows you how to build, deploy and defend AI systems with confidence using proven patterns, real code and production-tested techniques. Built for engineers who need security that works in the real world.

Build Model Context Protocol servers that go beyond demos. This hands-on guide walks you from the fundamentals to production deployment with practical examples in Python, TypeScript, Go, Rust and Java. Learn the patterns, tools and real-world practices needed to build secure, scalable MCP servers that are ready for enterprise AI.

AI coding agents can write code fast, but they need codebases built for collaboration. This book shows experienced engineers how to design, test and maintain software that works seamlessly with tools like Copilot, Cursor and Claude Code. Practical patterns, real projects and proven workflows help you build systems that scale with AI.

AI agents are only as good as the loops behind them. This book shows you how to build systems that plan, act, evaluate and improve with every step. Learn the patterns, frameworks and engineering practices behind reliable, self-correcting agents that solve real problems in production.

Build powerful AI agents that run entirely on your own hardware with Ollama. Learn practical patterns for RAG, multi-agent systems, security and deployment through clear explanations and production-ready code you can use right away. From first setup to reliable real-world applications, this book helps you build with confidence.

Go beyond prompts and learn how to build AI systems that hold up in production. This book shows how to make context the foundation of reliable LLM applications, covering practical patterns, real trade-offs and proven engineering techniques with clear examples you can put to work right away.

The future of AI depends on how we measure it. This book cuts through the hype to show what benchmarks really tell us, where they fall short and why better evaluation leads to better models. Practical, clear and grounded in real-world experience, it is an essential guide for anyone building, studying or deploying modern AI.

Build serious AI systems on NVIDIA DGX Spark with a practical guide that goes far beyond setup. Learn to deploy LLMs, create RAG pipelines, orchestrate AI agents, and optimize performance for real production workloads. Whether you are experimenting or scaling enterprise AI, this book shows you how to get there.

Evaluation Engineering for AI Systems is a practical guide to building reliable AI evaluations for production. Learn how to measure performance, compare models, detect regressions and create evaluation pipelines using real-world examples, modern Python and proven industry practices.

Discover how to unlock the full potential of Claude Opus 5 with a practical guide built on Anthropic's official documentation and proven best practices. From writing your first effective prompt to designing sophisticated agentic workflows and production-ready systems this book gives you the techniques, patterns and insights needed to achieve more accurate, reliable and consistent results.