AI agents are only as good as the loops behind them. This book shows you how to build systems that plan, act, evaluate and improve with every step. Learn the patterns, frameworks and engineering practices behind reliable, self-correcting agents that solve real problems in production.
ソフトウェア開発は急速に変化しており、Claude Codeはその変革の中心にあります。本書『Mastering Claude Code』は、AIエージェントと効果的に連携してコードを記述し、ワークフローを自動化し、より大規模なプロジェクトに自信を持って取り組むための方法を開発者に提示します。セットアップやプロンプト設計から実践的なエンジニアリング手法に至るまでを網羅した本書は、2026年における現代的なソフトウェア開発のあり方を理解したいすべての人にとって、実用的な指針となる一冊です。
AI coding agents can move faster than Git’s staging-and-commit workflow.Juju-chu! shows how Jujutsu🐦⬛ gives you automatic commits, reliable undo, and a safer way to reshape messy AI-generated changes—while staying compatible with Git and GitHub. For developers who already use Git and want a calmer AI workflow.
Build AI inference systems that run fast, use less memory and keep your data where it belongs. This hands-on guide walks you through model deployment, performance tuning, security and production engineering with practical code and real benchmarks. No cloud dependency, no surprise bills, just efficient AI systems you control.
Get more from Gemini 4 Argon with practical prompting techniques that work on real-world tasks. This guide covers coding, research, legal and financial work, long-horizon workflows, optimization and prompt evaluation, with clear examples and strategies for getting reliable results from one of the most capable AI models available.
Build AI systems that do more than demo well. This hands-on guide shows you how to engineer autonomous software on Linux that is secure, observable, reliable and ready for production. From agents and memory to threat modeling, OpenTelemetry and Kubernetes, you’ll build a real system while learning what it takes to run AI you can actually trust.
Local Intelligence shows you how to run large language models entirely on your Mac with Apple Silicon. Learn to use tools like Ollama, MLX, and llama.cpp, understand quantization, and build real local AI applications with open-source code.
Learn how large language models work instead of relying on black-box APIs. Building Large Language Models from Scratch takes you through training a Transformer model in PyTorch, from raw text to a working inference API, covering tokenization, attention, distributed training, and alignment along the way.
Learn how to build reliable AI agents with PydanticAI, from simple chatbots to production-ready multi-agent systems. With practical examples, clear explanations, and hands-on projects, this book helps you write AI applications that are structured, testable, and easy to maintain.
This book is a practical guide to building and running local AI systems in 2026. Learn how to choose hardware, run modern LLMs, build RAG pipelines and AI agents, and deploy secure, efficient infrastructure while keeping full control of your models and data.
AI changes the security game. New attack paths demand new ways of thinking. This practical guide shows you how to build, deploy and defend AI systems with confidence using proven patterns, real code and production-tested techniques. Built for engineers who need security that works in the real world.
A IA consegue escrever código mais rápido do que você consegue lê-lo, então, por que os projetos ainda saem dos trilhos? A resposta está na especificação. Este livro ensina o Spec-Driven Development na prática, construindo um aplicativo completo, ciclo a ciclo, com o Spec Kit. Pare de apenas enviar comandos e torcer para dar certo. Comece a entregar softwares que a IA realmente acerta.
Build Claude into a reliable specialist for your domain. The Claude Skills Handbook takes you from the first idea through architecture, implementation, testing, security, deployment and monitoring, with practical patterns and working examples throughout. Learn how to build Skills that scale, stay maintainable and work in the real world.
Die Softwareentwicklung wandelt sich rasant, und Claude Code steht im Zentrum dieses Wandels. „Mastering Claude Code“ zeigt, wie Entwickler mit KI-Agenten Code schreiben, Arbeitsabläufe automatisieren und auch komplexe Projekte effizient umsetzen. Praxisnah vermittelt das Buch Einrichtung, Prompt-Design und bewährte Engineering-Praktiken für moderne Softwareentwicklung im Jahr 2026.