Books

React Native got you far. But when performance, maintainability and long-term control start to matter, native development deserves another look. This book explores Swift, SwiftUI, Kotlin and Jetpack Compose, helping you understand when going native makes sense and how to make the move without losing what already works.

Build real-time data systems that can keep up with the demands of production. Streaming at Scale takes you under the hood of Apache Flink, covering state, event time, exactly-once processing, performance, Kubernetes and more. With runnable examples and practical lessons, it shows how to build systems that are fast, reliable and ready to scale.

Forget IShape — it's time to build software that actually does something. OrderFlow takes ten classic Gang of Four design patterns and weaves them into a single, fully functional food delivery platform built with C# and .NET 10. Clone the repository, step through the production-grade code, and finally master not just how to write patterns, but when to use them (and when to keep it simple).

AI can sound certain even when it is completely wrong. This book takes a practical approach to building RAG systems and AI agents that ground answers in evidence, verify what they generate and know when to stop. Learn how to make AI more reliable in the places where getting it wrong really matters.

Security is no longer something you add after a system is built. It must be designed from the beginning.Security by Design explores how modern digital systems can be built to reduce risk, limit unauthorized access, protect sensitive data, detect threats, contain failures, and recover from attacks.From secure architecture and cybersecurity foundations to privacy, cloud security, DevSecOps, AI security, and digital resilience, this book provides a practical foundation for building systems that remain secure in an increasingly connected and AI-powered world.

The Future of Software Engineering Has Arrived.AI can now write code, generate tests, analyze requirements, explain systems, assist with debugging, and automate increasingly complex engineering tasks.But building great software has never been just about writing code.How do you design the right architecture?How do you build systems that remain secure and reliable at scale?How do you integrate AI without sacrificing quality, privacy, or control?How do you use AI to make engineers more effective without replacing engineering judgment?Engineering Software Systems in the AI Era explores these questions and provides a practical framework for designing, building, testing, securing, deploying, operating, and evolving modern software systems.Inside, you will explore:Modern software architecture and system designCloud-native and scalable systemsData architecture and intelligent data systemsAI engineering and AI-native applicationsCybersecurity and privacy by designSoftware quality and reliabilityDevOps, DevSecOps, and continuous deliveryObservability and production engineeringAI-augmented software developmentAI agents and intelligent engineering workflowsPlatform engineeringTechnical debt and engineering strategyAI governance and risk managementTechnical leadership in the AI eraThe future of software engineeringThe central message is simple:AI may make software development faster. Engineering makes software better.Learn how to combine the power of artificial intelligence with the discipline of software engineering to build systems that are secure, scalable, reliable, intelligent, maintainable, and ready for the future.

Python is entering a new performance era. Explore free-threaded execution, Rust extensions and modern tools for building faster, more scalable Python systems. Learn how CPython is changing, when Rust makes sense and how to turn these ideas into production-ready software.

Git is much bigger than GitHub. This practical guide explores self-hosted platforms, decentralized approaches, secure operations and CI/CD beyond the usual defaults. Learn how to design, deploy and run independent Git infrastructure for real-world engineering, enterprise and regulated environments.

What if you could build software without manually writing every line of code? Artificial Intelligence is transforming the way software is designed, developed, tested, and deployed.But becoming an AI-powered software engineer isn't simply about asking an AI to write code.It's about learning how to think, design, build, test, verify, and improve software with AI as your engineering partner.The AI-Powered Software Engineer takes you on a practical journey from traditional programming to AI-assisted development and modern AI engineering.Learn how to use AI to:Design software. Generate and understand code. Debug complex problems. Build AI-powered applications. Automate workflows. Test and secure software. Deploy real products. Build AI-powered SaaS businesses.You don't need to become the fastest programmer in the room.You need to become the person who can turn an idea into a working, reliable, valuable system.Write less code. Think more. Build faster. Engineer smarter.The future of software engineering isn't humans versus AI.It's humans building with AI.

Static code analysis is more than running a linter and fixing warnings. This book shows how to build practical analysis pipelines with Claude Code and deterministic tools, combining AI-driven insights with reliable checks to improve code quality and security across projects of any size.

Good software is not about following rules. It is about knowing when they apply. This book explores the judgment behind building software that lasts, from choosing simplicity over cleverness to balancing today’s needs with tomorrow’s costs. Practical, thoughtful and focused on decisions, not dogma.

From the Linux basics to advanced development workflows, this practical guide shows you how to turn Linux into a powerful software development environment. Learn the command line, work with popular programming languages, use containers and CI/CD, debug and profile applications and build skills you can use every day.

What if AI could help you find flaws in software logic before they become costly bugs? This practical guide shows you how to use Claude Code alongside proven verification tools to test assumptions, uncover hidden issues and build confidence in your code. From first principles to production workflows, learn a smarter way to verify software with AI.

Abandona el ensayo y error en la IA generativa. Un marco práctico y metodológico basado en el falsacionismo de Karl Popper para auditar, estresar y dominar la interacción con modelos de lenguaje.

Build real machine learning applications with TensorFlow.js, from your first model to production-ready systems. Learn how to train and deploy models in the browser and Node.js, tackle real-world challenges and explore modern techniques with practical JavaScript and TypeScript examples you can run and adapt.