Artificial Intelligence

Turn AI into leverage, engineer your first $29 sale, and prove your business is real - in days, not months.

Essential Python libraries and frameworks that every aspiring data scientist, ML engineer, and Python developer should know.

Running LLMs with your own data allows you to quickly build personalized applications.

All examples in Hy. The Hy language (Lisp that compiles to Python) allows Lisp programmers access to the rich Python ecosystem for Large Language Models, deep learning, artificial intelligence, and general data wrangling. Applications: LangChain, Knowledge Graphs, NLP, Deep Learning.

A working engineer's guide to building and maintaining production software with autonomous terminal coding agents (382 manuscript pages).

Most agent books teach prompts and frameworks. Agent Engineering teaches the judgment and engineering discipline required to build AI agents that are reliable, secure, testable, and ready for production. Follow a practical Claude-based project from first agent to production-grade autonomous system—and receive every future update to this early-access edition.

Artificial Intelligence is transforming the world—but it is also creating an entirely new attack surface.What happens when attackers manipulate AI through language itself?Discover how cybercriminals exploit prompt injections, jailbreak models, steal sensitive information, and bypass AI guardrails. Through real-world examples, hands-on labs, secure coding techniques, and enterprise-ready architectures, Mastering LLM Security equips you with the knowledge needed to defend the next generation of intelligent systems.Whether you are building AI products, securing enterprise deployments, or leading cybersecurity programs, this book provides the blueprint for defending modern AI infrastructures.

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.

Most writing about AI and infrastructure stops at the demo. This book starts on the day the model is confidently wrong at 3 a.m. and an auditor asks who authorised the action it took. Seven working labs — MCP servers with real identity and audit, closed-loop remediation behind a reversibility gate, and autonomy that can be revoked — for platform engineers in safety-critical and regulated industries.

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.

The most truly passive online business I know is Amazon KDP. If you want to stay anonymous and build a passive online business system the hard way, this book is for you.

From quantum and molecules to cells, individuals, organizations, nations, and civilizations—why do clearly defined hierarchical structures emerge? Why does evolution often manifest as a repeating rhythm of "oscillation—stability—aggregation—re-stability"? Why do many systems fail not because of insufficient power or lack of information, but because the "pace of doing things" is wrong?

Stop selling hours and start owning systems that compound. This technical field manual provides eight executable "money identities" to help you graduate from trading time for dollars into designing AI-powered systems that generate "Agentic Wealth".

Throughout the book, we use a car-search platform as a unifying example. From ingestingdata about car listings to enriching, it with analytics and providing real-time search results, thisplatform showcases the challenges and opportunities of modern data platforms. By followingits journey, you will gain actionable insights that can be applied to a wide range of domains.Building the software platforms is not just about technology; it’s about solving real-worldproblems with creativity within the given guardrails both financial or engineering. This bookwill be guiding you through every phase of design, implementation, and evolution. Let’s buildthe future of data platforms together.

LLMs und Agentic AI sind derzeit Hype. Richtig angewendet können sie extreme positive Effekte bringen. Dieses Buch zeigt, vor welchen Herausforderungen man in großen Unternehmen und speziell auch in regulierten Umfeldern bei der Einführung stehen wird. Das Buch ist eine leicht lesbare Einführung für IT-nahe Führungskräfte und Enterprise Architekten und auch nützlich für IT-Profis allgemein, die in das Thema einsteigen möchten und absehbare Projektfehler vermeiden möchten