Artificial Intelligence

Stop guessing at prompts. This visual workbook gives you 50 ready-to-run workflows, command cheatsheets, and debugging checklists for Claude Code, Cursor, and GitHub Copilot — so you can open any page and immediately know what to type.

The intelligence is in the data. Learn to build AI systems that answer with grounded confidence, not fluent invention — through vector databases, RAG, and semantic search, from first principles to production-ready blueprints.

AI can generate an answer. But can it safely take action?AI agents are changing software by giving intelligent systems the ability to plan, use tools, interact with external systems, and execute multi-step workflows.Moving from an impressive prototype to a dependable production system, however, requires much more than a powerful model.AI Agents & Agentic Workflows in Production explores the engineering principles behind production-grade agentic systems—from architecture and tool use to memory, planning, orchestration, evaluation, security, reliability, observability, scalability, governance, and continuous operation.Learn how to build agents that don't just act—but act reliably, safely, measurably, and under control.

Unlock NVIDIA GPU performance from Rust. This practical guide takes you from GPU architecture and memory hierarchies to writing and optimizing real CUDA Rust kernels. Explore both official Rust CUDA approaches with runnable examples and learn how to build fast, production-ready GPU code without giving up Rust’s safety and clarity.

Most AIOps material is written by people selling AIOps. This one separates what works in production today from what is still a roadmap promise — and says which is which, chapter by chapter.

Ideas are abundant. Outcomes are rare.What happens when Forward Deployment evolves beyond an engineering role and becomes an enterprise operating capability?Idea to Outcome explores how enterprises can bring business context, engineering, AI and multidisciplinary teams together to move from discovery to deployment—and from activity to measurable outcomes.The distance between an idea and its outcome is where enterprise value is either created—or lost.

Stop choosing between an AI that's powerful and one you can certify. From Shannon's entropy to a reproducible, auditable Industry Language Model — built in C#, wrapped in Deterministic Islands, with every number independently verified.

Written for people who never asked to become AI users and now are. Not a tour of the technology, but a practical guide to working with it well — the habits that make good results repeatable, and the judgement to know when to check.

It is three in the morning and something is wrong with your LLM application. This is the book you open. Not a tutorial — a reference manual, organised by symptom, for the moment something you built has already broken.

AI evaluation agents crossed trust boundaries, reused credentials and coordinated through persistent shared state. This evidence-led reconstruction explains what happened, what remains unproven and how AgentSecOps can prevent the same architecture from failing again.

When machines can create compelling work, what makes human involvement matter? Explore the value of authorship, the experience of making, and the relationships that give creative work its meaning.

AI-generated content is everywhere, but how do you know what is real? The AI Forensics Handbook explores the science behind detecting synthetic text, images, video and audio, revealing the signals AI leaves behind and the methods used to uncover them. Practical, rigorous and grounded in real-world limitations, this is a guide to understanding what detection can really prove.

Every sentence an AI writes can carry a hidden signature, and the world's biggest models are already signing their output. AI Watermarking shows you exactly how it works, using a four-word vocabulary and arithmetic you can check with a pocket calculator. By the end you will know what a watermark can prove, what destroys it in seconds, and why short text can never be tested.

AI can sound certain even when it is completely wrong. This book takes a practical approach to building RAG systems and AI agents that ground answers in evidence, verify what they generate and know when to stop. Learn how to make AI more reliable in the places where getting it wrong really matters.

AI search is changing how customers discover what to buy, who to trust and which businesses to choose. The AI Visibility Handbook gives you a practical roadmap to get found, cited and recommended across ChatGPT, Google, Gemini, Perplexity and more. No hype, just clear strategies you can put to work.