Learn how modern LLM inference engines work by building one from scratch in Rust. From transformers and tokenization to KV caching, quantization, batching, and GPU optimization, this book combines theory, hands-on code, and performance engineering to help you create fast, production-ready AI systems.
Your ORM works until it doesn't: a query returns ten thousand duplicated rows, a migration refuses a partitioned table, or the feature the product needs is one PostgreSQL has had for years. Twenty-one chapters that close the gap — LINQ translation, query plans, JSONB, full-text search, PostGIS and pgvector, then auditing, multi-tenancy and deployment. Every listing run against a live database. Every output captured, never typed.
A practical guide to CPU affinity, NUMA, and thread placement for Java engineers who need nanosecond-precise, deterministic latency. Every example compiles against the open-source faster-hft-affinity library and is enforced by its test suite.
Learn to build fast, scalable asynchronous applications in C with libuv, the cross-platform library behind Node.js. Through practical examples and clear explanations, you'll master event-driven programming and write high-performance software that runs efficiently across Linux, macOS and Windows.
The fastest practical path to understanding harness-driven development as a complete system. Through clear visual diagrams and a real repository mapped to the book, you will see how a harness guides AI agents, evaluates their work, detects drift, enforces constraints, supports repair, and keeps software evolution visible, verifiable, and under control.
This practical handbook provides a step-by-step guide for you to get the best continuous delivery pipeline for your software.
Your use cases have a new reader: an AI agent that turns them directly into code and tests. Implementation is now cheap but expressing intent precisely is the bottleneck. This guide teaches you to write use cases that work for stakeholders, engineers, and the AI agents that implement from them.
This book will show you how to effectively use Ableton Live's capabilities to produce music, enhancing the standard of your musical endeavors and enabling you to confidently include production methods in your music projects.
본 책은 단순히 “코틀린을 어떻게 사용하는가”를 넘어, “코틀린이 실제로 어떻게 동작하는가”까지 안내합니다. 내부 구현을 들여다보고, 바이트코드와 컴파일러의 동작을 명확히 탐구하며, 언어를 형성하는 핵심 내부 구조를 파헤칩니다. 기초 문법부터 코루틴, 컴파일러에 이르기까지 더 깊이 이해하고, 더 자신 있게 코틀린 코드를 작성하고 싶은 분들께는 좋은 지침서가 될 것입니다. 특히, 우리가 일상에서 친숙하게 사용하던 모든 언어적인 형태가 왜 지금과 같은 형태로 설계되었는지를 탐구하며 사고의 깊이를 더할 수 있습니다. Hardcover | Paperback | ISBN: 979-8243872744 [Course] Practical Kotlin Deep Dive Course
This 2025 edition of Docker Deep Dive is a true masterpiece. The best-selling Docker book is up-to-date with the hottest Docker technologies and the latest industry trends. This edition includes a brand-new chapter on Docker Model Runner for fast, private LLM-based apps. You won't find a better and more up-to-date book on Docker. Hand-crafted and kept up to date over the past 9 years by best-selling author Nigel Poulton.
Need a quick introduction to running an effective EventStorming session? This book is a handy quick start guide for anyone wanting to learn how to facilitate an EventStorming session.
Fifty RF‑101 Voodoos arrived in Vietnam. Forty‑seven were shot down in a year. The pilots who survived didn't fly faster aircraft — they cycled through the OODA loop faster than the missiles chasing them. Jeff Sutherland was one of them. He went on to co‑create Scrum. Now, six decades later, he is running AI agents through daily sprints at machine speed — and this book is the playbook for how to do it without getting shot down.
Don't waste your time to learn how to code. That's what AI is here for. This book focuses on the far more profound question: What to code? This is the new meta skill between now and 2030!
The most important impact of AI on software development isn't that it writes code faster — it's that it changes what you can delegate. Agentic Programming is a practical roadmap for climbing the AI Fluency Ladder: from prompting to agentic workflows, verified execution, and ultimately autonomous software development.
Teams are producing more code than ever. Dashboards are green. And something is quietly breaking. AI coding assistants didn't break your development process; they revealed it was already fragile. Reimagine, Don't Retrofit is a field-tested argument that the software development lifecycle itself needs to be reimagined for the AI era, from governance and metrics to team roles and delivery flow.