Books

Unlock the full potential of Claude Fable 5 with a practical guide built for developers who are shipping real AI applications. From prompt engineering and agent orchestration to RAG, memory, safety, evaluation, and production deployment, this definitive reference delivers proven patterns, hands-on examples, and reusable templates to help you build reliable, scalable AI systems with confidence.

Master AI/ML System Design with a Structured Interview FrameworkLearn how to approach complex ML system design interviews using a 20-step framework, architecture blueprints, real-world case studies, scalability strategies, data and model pipelines, deployment patterns, monitoring, and interview-ready templates.

Stop guessing at prompts. This visual workbook gives you 50 ready-to-run workflows, command cheatsheets, and debugging checklists for Claude Code, Cursor, and GitHub Copilot — so you can open any page and immediately know what to type.

Rapid-development frameworks across Ruby on Rails, Node.js, PHP, Python, and .NET revolutionized how quickly we can ship software. But what happens when your business domain grows complex? Relying on Active Record and heavy ORM patterns tightly couples your database to your business logic. As your product matures, this coupling creates brittle, difficult-to-maintain codebases that resist change and slow down your team. The solution is the Domain Model Pattern (the foundation of Domain-Driven Design). It isolates business rules from infrastructure, creating a pure, scalable architecture. Historically, however, this pattern required a massive amount of effort and boilerplate, making it too slow for fast-paced development. That changes today. We are at an AI inflection point. Modern AI coding assistants excel at generating boilerplate and wiring infrastructure, effectively eliminating the traditional drawbacks of DDD. AI finally bridges the gap between the rapid speed of framework scaffolding and the architectural purity of a Domain Model. But to harness AI reliably, you cannot simply let it generate code unguided. You need a structured methodology to guide the machine. In this book, you will learn:How to build reliable, maintainable software using a strict, AI-assisted pipeline: Use Cases → Gherkin → Event Storming → Strategic & Tactical DDD.How to create implementation-agnostic class diagrams that serve as universal blueprints, allowing you to generate code in OOP languages (Java, C#, PHP, Python) or Functional languages (Elixir, Clojure, F#).How to future-proof your systems with a timeless methodology that prioritizes the longevity of business logic over the ephemeral nature of web frameworks.How to scale your architecture gracefully from a Majestic Monolith to Microservices without a complete rewrite. The methodology is language agnostics but in this edition all codes samples are in TypeScript. Whether you want to accelerate your development velocity, improve your system's resilience, or simply reclaim your craft by building beautiful, majestic systems, this book provides the blueprint.Discover how to combine the timeless principles of DDD with the power of AI.

《我的智能体：从聊天到 AI 工作台》写给已经重度使用 AI 智能体的人。它不再停留在提示词技巧，而是帮助你建立属于人的 Agent Control Plane：任务、证据、变更与接管。

Os agentes de programação com IA avançam rápido. O fluxo de trabalho do Git, baseado em staging e commits, nem sempre consegue acompanhar esse ritmo.Juju-chu! mostra como usar o Jujutsu🐦‍⬛ para registrar commits automaticamente, desfazer operações com confiança e reorganizar com mais segurança as alterações difíceis de organizar que a IA gera. Tudo isso mantendo a compatibilidade com o Git e o GitHub. Para desenvolvedores que já usam o Git e querem um fluxo de trabalho com IA mais tranquilo.

Los agentes de programación con IA pueden avanzar más rápido de lo que permite el flujo de trabajo de Git basado en staging y commits.Juju-chu! muestra cómo Jujutsu🐦‍⬛ te da commits automáticos, una forma confiable de deshacer operaciones y una manera más segura de reorganizar los cambios desordenados que genera la IA, todo con compatibilidad total con Git y GitHub. Para desarrolladores que ya usan Git y quieren un flujo de trabajo con IA más tranquilo.

The loop writes code and clears context. The commit log records MAX_RETRIES = 3, but the reason it's three vanished on Friday night. The artifact survived; the decision evaporated.The Loop That Remembers inverts the premise: memory isn't the sixth piece, it's what the loop exists to produce. Two graphs, a promoted lattice, bounded context, and an evaluator checking claims against edges.

Turn AI-generated code into production software. Use observable requirements, architectural boundaries, TDD, review, release gates, security, payment, delivery, and operations to ship maintainable AI-assisted systems.

A working engineer's guide to building and maintaining production software with autonomous terminal coding agents (382 manuscript pages).

A working engineer's guide to building and maintaining production software with autonomous terminal coding agents (382 manuscript pages).

Die Nutzung von KI zum Programmieren ist einfach. Sie zu nutzen, ohne die Kontrolle zu verlieren, schon weniger. Spec-Driven Development ist die Methode, um deine Idee in eine Spezifikation zu verwandeln, die die KI präzise ausführt — ohne Endlosschleifen, ohne kaputten Code, ohne wieder bei null anzufangen.

Ein Coding-Agent liefert in Sekunden makellosen Code, mittendrin eine Funktion, die es nie gab: Halluzinations-Lasagne. Claude Shannons verrauschter Kanal von 1948 erklärt, warum plausible Ausgaben nicht verlässlich sind, und wie ein geschärfter Sender, ein beherrschter Kanal und ein prüfender Empfänger daraus verlässliche Software machen.

Whether you are new to AI or building advanced applications, The Prompting Playbook gives you the knowledge and practical techniques to communicate effectively with large language models. Packed with research-backed insights, real-world examples and actionable guidance, it helps you get better results from AI with confidence.

Master Codex CLI from your first prompt to production-ready AI workflows. Learn how to automate coding, streamline development, and use OpenAI's terminal-native coding agent with confidence.