Software Engineering

Learn how to build a modern programming language from scratch in Rust. By implementing a complete language called Rune, you will explore every stage of language design, from lexing and parsing to type checking, virtual machines, LLVM code generation, and developer tooling, with practical code and clear explanations throughout.

Build a source-level debugger in Rust from the ground up while uncovering the operating system, CPU, and compiler mechanisms behind modern debugging. Through hands-on implementation, you'll learn how processes, memory, breakpoints, and DWARF debug information come together to make source-level debugging possible.

Learn Lua from your first script to advanced programming techniques with a practical, hands-on guide. Whether you are building games, scripting applications, or exploring embedded systems, this book gives you the knowledge to write clean, efficient Lua code with confidence.

The Python interview guide written from the interviewer's side of the table. 35 chapters. Every benchmark measured. Every line of code verified. What senior engineers actually get asked — and what separates the ones who get the offer.

AI can generate code in seconds, but shipping production-grade software requires far more than fast prompts. Vibe Engineering shows you how to work with AI coding assistants to build systems that are reliable, secure, and maintainable. Through practical examples and proven workflows, you will learn how to turn AI from a code generator into a trusted engineering partner.

Artificial intelligence is reshaping financial markets. Intelligent Markets shows you how to build production-ready AI trading systems from first principles, combining market fundamentals, practical architecture, and fully runnable code to create autonomous agents that can research, execute, and manage trades in live markets.

Build fast, reliable, and scalable software with Go. From core language fundamentals to advanced concurrency, testing, and production deployment, The Golang Handbook guides you through every stage of modern Go development with practical examples and real-world techniques, helping you write clean, efficient code with confidence.

There's a reason your last incident made it past review. It's not that nobody tested — it's that nobody asked the right question. This book is 745 of the right questions, sorted by what happens if you skip them.

You already know the principles. Then you hit a wall mid-project — the session died, a decision turned out wrong, four pieces have to become one — and knowing the principles isn't the same as knowing what to do. Claude Patterns is ten reusable workflows for exactly those moments: the assemblies you run when principles alone don't get you through.

Build AI agents that do real work with the Google Agent Development Kit (ADK), Python, and Google Cloud. Through complete, runnable examples, you'll learn how to build, orchestrate, and deploy production-ready multi-agent systems with practical skills you can apply from day one.

Go beyond simple chatbots and build production-ready AI agents with LlamaIndex. Through practical projects and working Python code, you will learn to design reliable systems with retrieval, workflows, multi-agent architectures, observability, and deployment techniques for real-world applications.

Run powerful AI models directly in the browser with no servers and no cloud dependencies. LiteRT.js teaches you how to build fast, private, and production-ready machine learning applications using WebAssembly, WebGPU, and WebNN, with practical examples and performance-focused techniques throughout.

Learn how to build intelligent, production-ready AI agents with the OpenAI Agents SDK. Through practical Python examples and step by step guidance, you'll master everything from the fundamentals to advanced multi-agent workflows, tools, and deployment.

Build intelligent AI applications with LangChain using practical, production-ready Python examples. From intelligent agents and retrieval-augmented generation to scalable deployment and observability, this book equips you with the skills and architectural understanding needed to create reliable, real-world LLM-powered systems.

The Linux ext4 filesystem is one of the world's most widely used filesystems, but its internal design is often difficult to understand. This book provides a practical, implementation-focused guide to ext4, covering its on-disk structures, algorithms, and core subsystems with detailed explanations, production-quality code, and references to the Linux kernel source.