Artificial Intelligence

Turn OpenAPI schemas into exhaustive test suites, wire Pact contracts between services, and let semantic fuzzers hunt the bugs random ones miss.

Build testing agents that observe, reason, act, and evaluate on their own — with the guardrails that keep autonomy from becoming chaos.

L’intelligence artificielle peut écrire du code, mais elle ne décide pas seule de l’architecture. Apprenez pas à pas à concevoir une véritable application d’analyse Bitcoin avec Ruby on Rails, PostgreSQL et l’IA, même si vous débutez en programmation.

Stop writing every test by hand. Direct AI like an editor-in-chief — prompt, generate, curate — without ever shipping a test you don’t understand.

Teach an AI coding agent to drive a real browser. The SKILL.md format, the Playwright CLI, first-party Test Agents, and the token economics that made skills beat MCP.

Everyone has seen the demo. This book is about what comes after: an engineer's guide from promising agent prototype to a system you can trust with real work — 26 chapters through contracts, orchestration, reliability, cost, security, and the operator practice. Updated quarterly. Buy once — every update is free.

Artificial Intelligence is transforming how we work, create, and solve problems. Agent AI is a clear, jargon-free guide to Generative AI and AI Agents, explaining how modern AI really works and how to use it effectively. No programming or technical background required—just practical insights, real-world examples, and a roadmap to the future of AI.

Deep learning is transforming the world, and this book provides a clear, practical path to mastering it. Through concise explanations and hands-on Python examples, you will learn to build, train, optimize, and deploy neural networks with confidence for real-world applications.

Build enterprise PHP applications faster with AI-assisted coding, architecture, testing, security, APIs, databases, DevOps, cloud workflows, and practical reusable prompts.

PyTorch stops feeling like magic when tensors, shapes, autograd, and training loops finally make sense. Build your understanding from the ground up with clear explanations, runnable code, and no GPU required.

Built around the CISO's Decision Journey — a five-stage loop of Assess, Govern, Defend, Monitor, and Improve — this book across fourteen chapters moves from the AI threat landscape and the regulatory environment to threat modelling and red teaming, a layered security-controls architecture, AI incident response, the AI-assisted SOC, and a 90-day programme roadmap.

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