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  1. Software Estimation
    Software Estimation
    Estimation that Works
    Stephan Schmidt

     Your CEO asks for an estimate. Your engineer says "3 weeks." Your CEO responds "you have 3 days." Sound familiar? After 30 years managing engineering teams, I've learned that most estimation is pure waste—and the pressure to give "better estimates" destroys trust and team morale. This book reveals a counterintuitive truth: stop estimating so much. Only estimate when it directly drives decisions. Learn why software estimation is fractal (like measuring Britain's coastline), how to distinguish effort from duration, and why your team keeps "missing deadlines." Discover how to reframe engineering from a cost center (always fighting for budget) to a profit center (getting the resources you deserve). Written for CTOs and engineering leaders, this practical guide delivers immediately actionable frameworks based on real experience coaching dozens of technical leaders. No theory, no agile dogma—just honest advice on estimation that actually works.

  2. Protocolo Cero Deuda: Fortificación de Proyectos de MLOps y Python en Producción
    Protocolo Cero Deuda: Fortificación de Proyectos de MLOps y Python en Producción
    Cómo Evitar que el Código de Machine Learning Colapse en Producción. El Framework Esencial para MLOps y la Fortificación del Código.
    Gerardo Senattore

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

  3. System Design Mastery - Data Analytics and Machine Learning
    System Design Mastery - Data Analytics and Machine Learning
    Case Studies, Trade-offs & Scenarios
    Sameer Paradkar

    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.

  4. Por Dentro do Jetpack Compose (Edição em Português do Brasil)

    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.

  5. Jetpack Compose 内部原理 (简体中文版)

    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。

  6. Jetpack Compose 內部原理(繁體中文版)

    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。

  7. The AI Engineer’s Handbook: Building Intelligent Software in the Age of Agents

    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.

  8. Memory Dump Analysis Anthology, Volume 17

    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.

  9. Agentic Coding for beginners
    Agentic Coding for beginners
    Learn how to plan, build, and review software with Claude Code, Codex CLI and other similar tools
    Wasi

    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.

  10. Node.js Event Loop
    Node.js Event Loop
    Mastering Concurrency with Asynchronous Patterns and Non-Blocking Design in Node.js
    A. Jobaer

    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.

  11. Production Ready Data Science
    Production Ready Data Science
    From Prototyping to Production with Python
    Khuyen Tran

    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.

  12. Why We Still Suck At Resilience
    Why We Still Suck At Resilience
    Organizational Dynamics
    Adrian Hornsby

    Your organization does all the right things. They practice chaos engineering, GameDays, and load testing. They conduct incident reviews and operational readiness reviews. Yet the same types of incidents keep recurring. This book examines why resilience practices so often fail to build resilience, revealing the organizational dynamics that systematically transform learning mechanisms into compliance theater and what you can do to navigate them consciously.

  13. Nobody but Us: A History of Cray Research's Software and the Building of the World's Fastest Supercomputer

    A Cray Research veteran narrates how pioneers handled overwhelming complexity: pattern recognition anticipating Midway, systems thinking inventing magnetic core memory. Experience from one domain, applied in a new way, shaped supercomputing.

  14. The Other Half of Coding
    The Other Half of Coding
    What they Didn't Teach You
    Max Guernsey, III

    Ever wonder why things get harder over time? You were only taught half of coding. Learn the other half and reverse code rot.

  15. Engineering Manager’s Compass
    Engineering Manager’s Compass
    Insights for building effective engineering organizations
    Dunya Kirkali and Maxim Schepelin

    Whether you're stepping into your first management role or navigating a new company, this book shows you how to thrive by understanding the hidden rules that shape your role, building unshakeable team alignment, and mastering the art of planning in uncertainty. From decoding your company's DNA and organizational dynamics to turning vague ambitions into actionable plans, you'll discover practical frameworks that reveal why some engineering teams flourish while others get stuck in endless debates and missed deadlines. This is the book we wish we had when we first stepped into management.