Software Engineering

Build a real compiler from the ground up with Rust. Follow the journey from source code to native x86-64 machine code as you design Lumina, explore optimization and register allocation and tackle the practical challenges that come with building a production-quality compiler.

What does it take to turn an AI agent from a clever demo into something you can trust in production? This hands-on guide uses DeepSeek Harness to show how to build reliable, secure and observable agents, from a simple script to a production-ready service with budgets, tracing, evals and multi-tenant support.

Build reliable LLM applications from first prompt to production agent. AI Engineering Visualized uses memorable doodles, practical Python, RAG, evals, tool calling and safety patterns to help you ship AI systems that work on Monday.

AI is most dangerous when it's almost right. Fifteen essays on software engineering in the age of AI, read through the psychology of Alfred Adler, about the machine that is almost right, and about our almost-right responses to it.

Learn Go from language foundations to dependable command-line tools and production services. Visual explanations connect concurrency, networking, testing, security, diagnostics, and operations with practical implementation and troubleshooting.

Thirty-two short field essays for engineers, with practical checklists and questions for team discussion. From your first years on the job to leading your first team, use these accounts to examine a decision you face: what you believe, what you can check, and what remains uncertain.

Build a compiler from the machine up. Start with twelve bytes of machine code you encode by hand, and finish with a compiler whose ray tracer draws exactly what gcc's build of it draws.

Master Tcl 9.1 from the ground up with a practical guide that goes far beyond the basics. Explore the language, TclOO, metaprogramming, internals, C extensions and production architecture through clear explanations and runnable examples. Whether you are new to Tcl or upgrading, build the skills to write clean, reliable software.

Happy-path architecture is a myth. When downstream dependencies degrade, naive retries trigger thundering herds, thread pools exhaust in seconds, and dual-writes silently corrupt financial balances. Surviving Distributed Systems is an unvarnished, production-tested field guide for senior backend engineers. Packed with architectural diagrams and modern Java 21 code, this book teaches you how to design, isolate, and harden high-concurrency systems so they survive catastrophic cascading failures.

Build reliable distributed systems with Spring Boot, RabbitMQ and modern Java. Follow OrderFlow as it grows from a simple service into a production-ready event-driven platform, exploring architecture, messaging, observability, containers and the practical trade-offs behind every design decision.

Master the ideas behind Java concurrency, from threads, race conditions, and synchronization to CompletableFuture, virtual threads, and structured concurrency. With practical patterns, runnable examples, and a companion GitHub repository, this book helps you move from understanding concurrency to applying it in real programs.

In this book, one estate runs through all fourteen chapters. There are eight services across two regions, a hybrid link to an older data centre, a storefront that real customers use, and one service backed by a language model. We use OpenObserve for that, bring all the signals into it, shape the data until long-term storage becomes affordable, and then spend the rest of the time diagnosing the estate when it breaks. There won't be a feature tour here. The features don't stand the test of time, and the screenshots are even worse. What you'll find is a method. First, scope the flag, orient before acting, form a hypothesis you can disprove, test it against evidence rather than instinct, repair, verify, and add the prevention that stops the same failure twice. That loop works whatever platform you use.

Take a practical deep dive into modern Haskell development with GHC, Cabal, HLS and effect systems. Learn how the tools work under the hood, how they fit together and how to use them effectively in real production projects. Built for engineers who want to move beyond syntax and develop Haskell with confidence.

Stop asking one giant prompt to carry your whole software system. Context Driven Development teaches you how to give AI coding agents explicit requirements, architecture decisions, constraints, tasks, and verification loops so they can work inside a reliable engineering environment.

Explore the Software, Computing Architectures, Data Pipelines, and High-Performance Systems Behind Modern High-Energy PhysicsCERN is more than a particle physics laboratory. It operates one of the world's most demanding scientific computing environments, bringing together extreme data rates, heterogeneous hardware, distributed storage, high-performance networking, real-time processing, large-scale simulation, machine learning, and advanced software engineering.Coding CERN: A Technical Developer's Guide explores the computing architecture behind experiments at the Large Hadron Collider (LHC), connecting detector electronics and real-time trigger systems with modern C++, ROOT, distributed computing, GPU acceleration, machine learning, high-performance computing, and global scientific infrastructure.The book takes a developer-oriented approach to the complete scientific computing pipeline, examining how physical events become digital signals, how those signals are filtered and reconstructed, and how the resulting data is stored, distributed, simulated, and analyzed across geographically dispersed computing facilities.