Books

"Your stack is not the tools you buy. It is the system you build."Selling used to be personal — carried in memory, known by name, and lost when the person left. Now it runs on software: data, automation, and AI that never sleeps, never forgets, and increasingly decides for itself.But more tools do not make a better system. Too many teams accumulate products like a junk drawer — overlapping, disconnected, and drowning in capabilities they never fully use. What matters is not what you add, but how it all fits together.From CRM foundations to autonomous AI agents, from data hygiene to ethical governance — here is the clear, practical framework to design your stack from the ground up: clean, connected, human-guided, and built to last. No vendor bias, no hype, just the architecture that will still work when today’s newest tool is obsolete.

Build one real app, from the first ionic start to a signed release, with Ionic 9, Angular 22 and Capacitor 8. Every starter, build and test in this book was checked against the real toolchain, and the app's code along the way is waiting in a public repository.

"Your team is already hybrid. The only question is whether it is designed."AI arrived quietly — one prompt, one draft, one spreadsheet at a time. Now your team works faster than ever. But do you know who verifies what? Who is accountable when the answer is wrong? Who hides their use, and who worries they will be replaced?This is not a technology problem. It is a design problem.From mapping your work to setting boundaries, from assigning roles to leading the conversation about what AI cannot do — here is the complete practical framework to lead your team alongside AI. No code, no hype, no big-bang transformation. Just clear management, honest conversation, and a plan that works.You do not need to be technical. You need to be clear.

100 AI alata. Koji vam zaista trebaju? AI Almanah 2026 pomaže vam da izaberete prave alate za svoj posao, razumijete njihove cijene i ograničenja i izbjegnete nepotrebne pretplate.

AI is changing how we work, learn and live, but understanding it does not have to be complicated. This practical guide explains how modern AI and LLMs work, what they can do, where they fall short and how to use them effectively without the hype.

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.