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Great software developers—even the proverbial greybeards—get a little better every day by adding knowledge and skills continuously. This new book invites you to share a cup of coffee with senior Google engineer Teiva Harsanyi as he shows you how to make your code more readable, use unit tests as documentation, reduce latency, navigate complex systems, and more. [Read more]

All chapters of this MEAP are available now!

When DeepSeek started making waves in January 2025, it sounded too good to be true. How could a generative AI model get such incredible performance with such low training and operation costs? In this guide, you'll find out exactly how DeepSeek works by recreating a laptop-scale version of this cutting-edge model yourself! [Read more]

CUDA (Compute Unified Device Architecture) provides a powerful parallel programming model AI engineers can use to tap the massive processing power of NVIDIA GPUs. This guide shows you how to work within the CUDA ecosystem, from your first kernel to implementing advanced LLM features like Flash Attention.[CUDA for LLMs]

All chapters of this MEAP are available now!

Data-oriented programming is a programming technique that enables you to precisely model domains and write large enterprise-scale applications that are oriented around the data they manage. Take a data-oriented approach to your Java applications, and you’ll enjoy simpler state management, improved readability, and no more state-related bugs! [Read more]

All chapters of this MEAP are available now!

Unlock the part of AI development that usually gets overlooked: everything required to make an AI system reliable, manageable, and ready for production. With complete Python code in every chapter, you’ll build a working reference implementation you can adapt to your own needs. You’ll also learn the practical operational skills that matter in production, including managing costs, routing requests, enforcing safety controls, and evaluating system quality. [Read more]

All chapters of this MEAP are available now!

Generating code with AI can feel effortless, but it’s only one part of software engineering. A production-grade development pipeline includes testing, validation, refactoring, optimization, and deployment. This book shows you how to go from AI-assisted coding to a AI-infused full-spectrum process author Tomasz Lelek and Artur Skowroński call vibe engineering. [Read more]

All chapters of this MEAP are available now!

With open models and open-source tools

Online image generators are powerful—but can you use them to get the results you actually want? Offline, locally hosted image generation models like Stable Diffusion give you the power to deeply customize your image with your own styles, characters, and ideas. In this practical and entertaining guide, you'll learn how to generate, refine, and customize images locally with Stable Diffusion—without needing a background in data science or machine learning. [Read more]

All chapters of this MEAP are available now!

The responses from Large Language Models (LLMs) are more accurate, consistent, and explainable when you provide specific relevant information, or context, to support your prompts. Context engineering is the discipline of selecting, organizing, updating, compressing, prioritizing the precise context a model needs to generate accurate responses. This book shows you how to combine well-designed prompts with smart search, content filtering, and advanced RAG techniques incorporating many types of stored data to create reliable responses in your AI applications. [Read more]

All chapters of this MEAP are available now!