Software Engineering

Everyone blames development for being slow. But what if the real bottleneck isn't your engineering team at all? After 25 years as an engineering manager and CTO, and 8 years coaching technology leaders through their biggest challenges, Stephan Schmidt has discovered an uncomfortable truth: you can squeeze out 10-20% by optimizing development, but you'll never reach the next level that way.  The real lever? Decisions. Meetings. The six months an idea bounces around before anyone writes a line of code.  This mini-book shows you how to measure and optimize the entire journey from idea to revenue—not just the coding part. You'll learn 10 practical rules to slash time to market, including how to build a decision culture that doesn't stall, why working in parallel actually slows you down, and how understanding MVP stages can free up development capacity.  Stop blaming your developers. Start fixing what actually matters.

Build a real-world digital banking platform from scratch using .NET 10, Clean Architecture, DDD, Angular 21 (Nx Monorepo), Docker, PostgreSQL, and GitHub Actions CI/CD. This hands-on, full-stack guide shows you how fintech systems are built in modern software teams—covering microservices, secure APIs, authentication, event-driven architecture, automated testing, containerization, and more. No shortcuts, no toy examples. Just real engineering.

Most products burn millions chasing growth, only to watch users leave as fast as they arrive. This book shows you how to build self-sustaining loops where every user makes your product faster, stickier, and more valuable, turning expensive acquisition into compounding, unstoppable momentum. Stop running on a treadmill. Start building a flywheel.

El Framework MLOps para eliminar la Deuda Técnica de Python IA en producción. ¡Garantía Cero Fallos!

Master Data and ML Systems at ScaleYou don't master data platforms from textbooks — you master from solving real problems at petabyte scale.System Design Mastery - Data Analytics and Machine Learning teaches through production scenarios and case studies. 100 scenario-driven case studies covering:✅ Lakehouse architecture with Delta Lake, Iceberg, Hudi✅ Real-time pipelines with Kafka, Spark, Flink✅ Feature stores with Feast for training-serving consistency✅ MLOps platforms with MLflow, SageMaker, Airflow✅ Data quality frameworks with Great Expectations✅ Multi-region data sync and model serving at scale Every scenario includes: production challenge, architectural trade-offs, data/ML patterns, decision frameworks, and interview-ready explanations. Learn through real-world case studies from Netflix, Uber, Airbnb, Spotify's petabyte-scale data and ML architectures. Your journey from data engineer to architect begins here — with scenarios you'll face and systems you can build.

O Jetpack Compose é o futuro da UI do Android. Domine como ele funciona internamente e torne-se um desenvolvedor mais eficiente com ele. Você também achará útil mesmo se não for um desenvolvedor Android. Este livro fornece todos os detalhes para entender como o Compose compiler e o runtime funcionam, e como criar uma biblioteca cliente usando-os.

Jetpack Compose是Android界面开发的未来。掌握其内部工作原理，让您成为更高效的开发者。即使您不是Android开发者，这本书对您来说也很有价值。本书详细介绍了Compose编译器和运行时的工作原理，以及如何使用它们创建客户端库。

Jetpack Compose 是 Android 使用者介面的未來。透過深入了解其內部運作原理，你將成為更有效率的開發者。即使你不是 Android 開發者，這些知識對你來說也很有價值。本書提供所有細節，幫助你理解 Compose 編譯器和執行時期是如何運作的，以及如何使用它們來建立客戶端程式庫。

The history of software engineering is a story of continuous abstraction. We moved from machine code to assembly, from assembly to compiled languages, and from monolithic applications to microservices. Each step simplified the how of computation, allowing us to focus on the what.Today, we stand at the precipice of the most profound abstraction yet: Intelligence.This book is the field guide for that transition. It’s written by someone who has been in the trenches, shipping intelligent systems across continents, from solving scale issues in Silicon Valley to architecting robust, low-bandwidth solutions in Lagos. It’s a practical, no-hype look at what works when building intelligent software.Read it, absorb it, and be prepared to transition from a code writer to an architect of intelligence.

This reference volume consists of revised, edited, cross-referenced, and thematically organized articles from the Software Diagnostics and Observability Institute and the Software Diagnostics Library (former Crash Dump Analysis blog) about software diagnostics, root cause analysis, debugging, crash and hang dump analysis, and software trace and log analysis written from 15 April 2024 to 14 November 2025.

Agentic coding is transforming how developers write software. Instead of relying on static code completion, you now collaborate with autonomous AI agents that plan, execute, and improve with you. Agentic Coding for Beginners introduces this new era of intelligent development through practical, tool-agnostic lessons. You’ll learn to plan, build, and review software with AI agents, using real, runnable code and real tools: Claude Code, Codex CLI, Copilot, Cursor, and agent harnesses such as Pi. You'll walk away knowing how to steer an agent well and catch it when it's wrong.

What happens when machines stop merely assisting developers and start thinking with them?Developer Productivity and Cognitive Automation takes you inside the next evolution of software engineering: where AI becomes your co-creator, automation becomes cognitive, and productivity is measured not in lines of code, but in focus, creativity, and flow.Through vivid stories, from high-pressure fintech teams in Lagos to AI-powered engineering squads in the UK, the book unveils how the smartest organizations are redefining “developer productivity” around mental energy, collaboration, and innovation. Whether you’re a coder, team lead, or tech executive, this book shows you how to build systems that amplify human intelligence, not replace it

Every Node.js developer uses asynchronous code but only a few truly understand what happens behind the scenes. This book reveals the internals of the Node.js Event Loop, including microtasks, macrotasks, and concurrency under load. You'll learn to master performance, scalability, and non-blocking architecture at a level that sets professionals apart.

STOP building fragile AI wrappers. START designing resilient AI systems. Lots of companies are trying to make their small AI experiments into big products, but they don't have a good plan. Engineers need a practical guide to build these new AI systems the right way - so they can handle scale, be reliable, and won't cost too much. This book is that guide. It explains how to design systems that use AI models. This book breaks down the architecture of real AI applications, like an AI-powered code editor or a smart learning app. It gives you a deep, practical look at the real-world challenges and solutions for building these systems. It discusses system design concepts for systems that use LLMs.

Are you a data scientist or analyst struggling to take your Jupyter Notebook prototypes to the next level? Have you encountered challenges with code organization, reproducibility, or collaboration as your data science projects grow in complexity? This book is the solution you’ve been seeking. This comprehensive guide bridges the gap between data analysis and software engineering, providing you with the essential tools and best practices to transform your data science projects into scalable, maintainable, and collaborative solutions.