Books

Turn a small language model into an AI agent that runs on your own hardware. This practical guide takes you from choosing a base model to fine-tuning, tool use, evaluation and deployment. With reproducible code and real configurations throughout, you'll learn how to build specialized local agents that are capable, efficient and truly yours.

Specification Engineering turns complex ideas into clear, workable specifications. This practical guide takes you from core principles to advanced methods for defining, validating, managing and evolving requirements across products, software, systems and services. Built for real-world use, it gives you the tools to create specifications that people can understand and act on.

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.

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 become truly powerful when they can reason, adapt and recover instead of following a fixed sequence of steps. This book shows you how to design intelligent agent systems with computational graphs, giving you the tools to build scalable, reliable applications that can handle real-world complexity 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.

Whether you are new to AI or building advanced applications, The Prompting Playbook gives you the knowledge and practical techniques to communicate effectively with large language models. Packed with research-backed insights, real-world examples and actionable guidance, it helps you get better results from AI with confidence.