Beginners Yoga House

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New MEAP! Spring Start Here, Second Edition

Spring Start Here, Second Edition by Laurenţiu Spilcă is a foundations-first introduction to the Spring framework. Perfect for Spring beginners, it steadily builds understanding through practical projects that explore the main ideas of Spring: configuration, beans, web endpoints, data access, and application structure.

Fully updated for Spring Framework 7 and Spring Boot 4, this practical book prepares you for fast development, clean application design, efficient cloud-native systems, and reliably-secure applications. Along the way, you’ll learn some best practices for applying your knowledge of Spring fundamentals when you’re using AI and agentic coding tools. [Read more]

10 chapters of this new MEAP are available now with more to follow soon!

SAVE HALF until July 16

Build Applications with Local AI Models on a Mac

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More new MEAPs

Create private chatbots, voice apps, RAG systems, and more

Learn how to make your own ChatGPT-like app, running 100% offline. Along the way, you’ll install and manage multiple models (Llama, Gemma, Qwen, Mistral) through Ollama, set up a professional Python environment from scratch with Homebrew and VS Code, and master Streamlit’s elegant Python-only UI framework. Architectural diagrams, flowcharts, sequence diagrams, and side-by-side comparison tables bring abstract concepts to life. [Read more]

Build consistent, accurate, predictable AI systems

Context Engineering

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]

Building LLM Applications with DSPy

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Replacing manual prompts with systematic optimization

Static, over-engineered prompts quickly lose effectiveness as models and data change. DSPy replaces inflexible text-based prompts with dynamic contract-based Python code, so your prompts can freely adapt and scale. In this practical guide, you’ll learn how DSPy automatically optimizes context, evaluates prompt effectiveness, and automatically tweaks your prompts as models drift and change. As you go, you’ll get tips and techniques to maintain stable inference results as your apps and agents evolve. [Read more]

Principles, patterns, and best practices

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Designing AI Agents

Learn how to establish agent architectures that manage costs and take governance seriously from day one. This innovative book explores 27 reusable patterns that you can apply to your own agentic systems confidently. Each pattern has been stress-tested at scale, with over 10,000 engineers applying them to ship production agents in banks, manufacturers, and AI startups. You’ll appreciate how this book guides you toward system and harness design that impose certainty and reliability on the non-deterministic behavior of LLM-driven agents. [Read more]

Web Component Development with Modern Libraries and Tooling

Build, test, and scale framework-agnostic web components

In this practical and easy-to-follow guide, author Mark Volkmann shows you how Web components deliver something no JavaScript framework can match: true portability. Built on W3C standards and supported natively by every modern browser, web components let you build UI elements once and reuse them anywhere, in React, Vue, Angular, Svelte, plain HTML, or even Markdown documents. No framework downloads and no immovable dependencies. [Read more]

Crack Any Codebase with AI

Code is free, understanding is not

Use an efficient AI-driven process to quickly and accurately make sense of any software project in just a few hours, complete with prompts, workflow pipelines, and mental models. Author and Microsoft AI researcher Zachary Huang argues that in an AI-first environment, the developers who thrive will be those who build architectural thinking rather than passively accepting AI’s output. The book transforms this thesis into a hands-on training program, reframing AI code’s flaws as workout opportunities for your skills as a developer. [Read more]