Books

You've set up your agent and taught it your name. With this book you teach it your patterns, your triggers, and the version of yourself you're working towards. 24 chapters. All prompts, no code.

You already know the principles. Then you hit a wall mid-project — the session died, a decision turned out wrong, four pieces have to become one — and knowing the principles isn't the same as knowing what to do. Claude Patterns is ten reusable workflows for exactly those moments: the assemblies you run when principles alone don't get you through.

Learn how large language models work by building one from scratch. This hands-on guide walks you from first principles to a working Transformer you understand inside out.

Advanced Prompt Engineering for LLMs: 2026 Techniques That Actually Deliver Results takes readers beyond basic instructions and introduces a complete system for working with modern Large Language Models.Discover how to:• Apply powerful frameworks such as RACE and TREE • Build advanced multi-layer prompts • Use meta-prompting to create and improve prompts • Design specialized expert personas

Discover the mathematics powering the future of Artificial Intelligence and cybersecurity.Algebraic Foundations of AI: Groups, Rings, and Fields in Security & Cryptography reveals how abstract algebra forms the backbone of modern AI security, cryptographic systems, blockchain technologies, privacy-preserving machine learning, federated learning, and post-quantum cryptography.

Become a better data scientist by understanding different modeling mindsets.

Una guida pratica a Claude Code, scritta con Claude Code.Su Claude Code circolano due tipi di contenuti: video YouTube che si fermano ai primi dieci minuti e thread social che promettono "guide complete" in cambio di un'email. Questo libro nasce dall'esigenza opposta: avere finalmente un manuale che spieghi lo strumento per intero, senza hype e senza muri di lead generation.140 pagine costruite a partire dalla documentazione ufficiale Anthropic, verificate su Claude Code v2.1.123, con esempi reali invece che screenshot da marketing. Si parte dall'installazione su macOS, Linux e Windows, si passa per Plan Mode, CLAUDE.md, gestione del contesto, sicurezza dei permessi, Skill personalizzate, subagent custom, integrazione MCP, e si arriva al prompt engineering aggiornato al 2026 — quello vero, dopo che le formule magiche del 2023 si sono sgonfiate.Il libro è pensato per due lettori in parallelo: lo sviluppatore senior che vuole integrare Claude Code nel proprio workflow di produzione, e chi si avvicina per la prima volta agli strumenti AI agentici e ha bisogno di una mappa. I capitoli iniziali costruiscono le basi senza dare nulla per scontato; quelli avanzati entrano nei meccanismi che fanno la differenza tra un uso superficiale e uno strategico.Tre cose che troverai e che altrove fatico a trovare:Il prompt engineering riletto al 2026. Niente ruoli posticci, niente "agisci come un esperto di...". Le tre leve che contano davvero — istruzioni esplicite, contesto adeguato, esempi curati — applicate al contesto specifico della CLI.Workflow reali, non demo da slide. Esempi concreti su WordPress e Node.js presi da progetti veri, non da repository giocattolo.In apertura c'è una prefazione scritta da Claude Opus, a cui ho dato il manoscritto completo chiedendogli un commento onesto, anche dove il libro non funzionava. È rimasta lì come l'ha scritta: è il modo più trasparente che mi sia venuto in mente per inquadrare il libro.Il libro è gratis — pay-what-you-want con minimo zero. Se ti torna utile e vuoi contribuire, decidi tu quanto. Se non puoi o non vuoi, scarichi e leggi senza pensieri: la licenza Creative Commons BY-SA 4.0 ti permette anche di redistribuirlo e modificarlo, basta citare la fonte e mantenere la stessa licenza.

You have been using AI as a faster keyboard.The engineers who will define the next decade are using it as a cognitive workforce they direct, constrain, and govern. The gap between those two practices is not a matter of better prompts. It is a matter of an entirely different mental model.This book is that mental model. Built from first principles. Illustrated through 28 chapters of real architectural decisions, real failures, and real production systems.From execution to orchestration. The complete practitioner guide.

Learn LangGraph the fast, practical way by building real projects from your very first chapter. This hands-on guide cuts out the fluff and walks you step-by-step from simple graphs to powerful AI agents like ReAct and RAG. If you prefer learning by doing, this book will get you up and running quickly without overwhelming you.

Large Language Models are powerful, but they're trapped. They can't access real-time data, call APIs, or even count characters reliably. *Practical MCP* is your guide to setting them free. Learn the Model Context Protocol (MCP), the "USB-C for AI" that standardizes how LLMs connect to the outside world. This book teaches Python developers everything they need to build, secure, and deploy powerful AI tools. You'll master integrating with Claude, Gemini, and GPT; create interactive tools that ask for clarification; and automatically generate an MCP interface for any REST API. Go from a simple "Hello, World" to deploying a full-stack, multi-service AI application in the cloud. Stop hitting the LLM wall. Start building the solutions. This book shows you how.

AI-Assisted Development verspricht Geschwindigkeit – aber Vibe Coding liefert oft Chaos. EXACT Coding zeigt, wie Software-Craft-Prinzipien und TDD als Korrektiv wirken: für Code, der schnell entsteht und trotzdem hält, was er verspricht.

Elevate your skills from programmer to architect and command the final frontier of Python.[1] Master advanced internals, high-performance concurrency, and the magic of AI orchestration. Build stateful agents with LangChain and RAG to create intelligent, enterprise-grade systems. Your expedition reaches its pinnacle—start building the future of AI-driven software today.

"Data Science Project: An Inductive Learning Approach" provides a comprehensive methodology for data science project development, emphasizing software engineering principles essential for reliable solutions. Dr. Filipe Verri, a senior data science project manager, guides readers through the origins, scope, and key concepts of data science. This book covers machine learning, data handling, and rigorous validation techniques, all essential for preparing readers to tackle complex, real-world projects.

Not another AI coding tutorial. A DX engineering book on using Claude Code to reduce developer friction - backed by METR, DORA, and Faros AI data. Processes first, then tools. 80% deterministic, 20% AI.

The book is free — pay-what-you-want with a $0 minimum. If you find it useful and want to contribute, you decide how much. If you can't or don't want to, just download and read without worry: the Creative Commons BY-SA 4.0 license even allows you to redistribute and modify it, as long as you credit the source and maintain the same license.