Books

The EU AI Act is changing the rules for anyone building, buying or using AI. This practical guide cuts through the legal complexity and shows what compliance actually requires. With clear explanations, real-world cases, templates and checklists, it gives leaders and teams the tools to turn regulation into workable AI governance.

The loop writes code and clears context. The commit log records MAX_RETRIES = 3, but the reason it's three vanished on Friday night. The artifact survived; the decision evaporated.The Loop That Remembers inverts the premise: memory isn't the sixth piece, it's what the loop exists to produce. Two graphs, a promoted lattice, bounded context, and an evaluator checking claims against edges.

What if your AI didn’t just answer questions—but solved problems?Imagine an AI that doesn’t just chat—it plans, reasons, and takes action. An AI that can fetch data, run diagnostics, collaborate with other agents, and even handle your most tedious tasks—all while you focus on what matters.Google’s Agent Development Kit (ADK) makes this possible,

Go beyond using AI tools—learn to build AI solutions. AI Generalist Engineer is a practical guide for software engineers, architects, and technology leaders to master enterprise AI, AI agents, RAG, MCP, prompt engineering, orchestration, and modern AI architecture. Build the skills to design, integrate, and lead AI-powered systems with confidence.

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.

当 AI 能替你写代码，真正的危险不是它写错，而是你以为它不会错。

An AI asked to build a network and its own tooling refused — no human had signed. Six weeks later the same machinery governed bare metal serving a 740B-parameter model, every step on a committed record. This book builds that lab from the ground up: the gate, the run records, the GitLab nervous system, the audit trail — AI doing real infrastructure work you can prove afterwards.

从任务、基线和证据出发，验证 AI 的真实价值。为个人、管理者与中小企业建立责任链、趋势判断、持续学习，以及停止、导出、迁移和恢复能力。

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.

Eight agents, zero coordination, one identical error. That's not a coincidence. It's a signature. Learn to read the five families of failure behaviors in multi-agent systems, reproduce each one in TypeScript, and turn every bias into a CI assertion before it ships.

From your first JAX script to large-scale AI systems, this book shows how to write faster, cleaner Python for modern computing. Learn the ideas behind JAX through practical examples, real projects and clear explanations that help you build everything from scientific simulations to distributed machine learning.

Um colaborador produtivo que escreve mais código que o time todo, mas esquece tudo com frequência. Quando não sabe, não hesita: inventa, confiante e errado. Você precisa aprender a trabalhar com ele: uma memória viva que mantém vocês na mesma página e um fluxo de trabalho que mantém tudo no lugar e funcionando. Dominar isso impede o agente de derivar e permite, enfim, produzir software de verdade.

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.

A IA mudou a forma de escrever código, mas o verdadeiro impacto está na engenharia de software. Este livro explica por que especificação, arquitetura e contexto passaram a ocupar o centro do desenvolvimento moderno.

Cloud, Kubernetes, AI, security and automation have changed what DevOps really means. This book cuts through the hype with practical guidance for building reliable, scalable platforms using proven patterns, real production lessons and modern engineering practices that help teams move faster without sacrificing stability.