Books

Теория информации: от энтропии и кодирования до NLP, LLM, компьютерного зрения и обучения с подкреплением. Обновлённые PDF/EPUB и бесплатная практика на vladkulikov.com.

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.

A free, developer-friendly guide to prompt engineering in C# — no Python required. Learn how LLMs work, structure reliable prompts, and build real workflows (code review, test generation, docs) using Microsoft.Extensions.AI, LM Studio, OpenAI, or Azure AI Foundry. Seven chapters. Seven runnable .NET 10 projects. Zero hype. Just dotnet new console and working code.

دليل عملي يجمع 50 من أهم أدوات تكنولوجيا التعليم التي تساعد المعلمين على إدارة الصف، وتصميم المحتوى، وإنشاء الأنشطة التفاعلية، والاستفادة من الذكاء الاصطناعي داخل العملية التعليمية.

The tool made you fast before it made you good. The Sovereign Apprentice is the regime that rebuilds what fluency skipped — judgment, verification, and a craft that's actually yours. Companion to The Sovereign Engineer.

ဥပမာအားဖြင့်၊ သင်က AI ကို "မိုးရွာရင် ထီးယူသွားပါ" ဟု ခိုင်းထားလျှင်၊ မိုးသည်းထန်စွာ ရွာနေသော်လည်း အိမ်ခေါင်မိုး ပြိုကျနေပါက ၎င်းသည် ထီးကိုသာ ကိုင်၍ အိမ်ထဲတွင် ငုတ်တုတ်ထိုင်နေပေလိမ့်မည်။ အဘယ်ကြောင့်ဆိုသော် "အိမ်ခေါင်မိုး ပြိုလျှင် ပြေးပါ" ဟူသော စည်းမျဉ်းကို သင်က ထည့်မပေးထား သောကြောင့် ဖြစ်သည်။

This book gives senior technology leaders a practical operating system for enterprise AI strategy. It turns scattered pilots into a board-ready plan by walking through strategy, economics, vendor decisions, ownership, governance, GenAI architecture, and roadmap assembly: AI Platform Scorecard, Use-Case Prioritization Matrix, Budget Model + Cost Guardrails, Vendor Decision Framework, RACI Matrix.

Do you love commercial coding agents like Google Antigravity and Claude Code? So do I! However I often use local agentic coding tools and this book will help you get started quickly.

Reliable Generative AI bridges business use and technical architecture. It teaches the foundations of prompt design, RAG, agentic workflows, tool use, structured outputs, safety patterns, and evaluation without assuming the reader is a software engineer. The focus is practical: understanding how AI workflows fail, how to design around those failures, and how to build systems that professionals can trust.

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.

This book familiarizes readers with the world of LLM and agentic AI, and helps them quickly gain a working-level knowledge of building useful agentic AI solutions for process industry operations. With no prerequisites required, practical demo applications, and a hands-on approach adopted throughout, this book makes advanced AI technologies accessible to process engineers and data scientists alike. It aims to help process data scientists and engineers take their first confident steps into Agentic AI world, understand the full picture, and build a strong enough foundation to keep learning and building on their own. Also available here.

A practical field guide for using AI assistants at work—and engineering them in production. Learn the standards that prevent “sounds right, wrong” outputs: specs, grounding, tools, evals, guardrails, and cost control.

if you've read my chapter on naming in a famous software book (first or second edition) you may want to go a little deeper. Same author, same topic, all-new content!

Elegant Design Principles distils decades of design wisdom into 95 actionable principles spanning core OO, SOLID/GRASP, package design, reliability and a forward‑looking AI‑first approach. Explore the Design Pyramid to understand how quality attributes, smells and principles interconnect; learn to manage complexity through high cohesion, low coupling and clear abstractions; and adopt modern practices like test‑driven development and semantic modularity. From novices seeking a roadmap to experts embracing AI‑assisted workflows, this book equips you to create systems that are robust, maintainable and elegant—today and in the AI‑driven future.