Computers and Programming

A Deep Systems Engineering Guide to ELF64 Internals, Dynamic Linking, Kernel Loading, Binary Instrumentation, and Executable Runtime ArchitectureEvery executable binary contains more than machine instructions. It encodes the structural information, symbol relationships, relocation rules, memory mappings, and runtime metadata required to transform compiled code into a functioning process. Understanding this transformation requires looking beyond compiler output and examining the mechanisms that connect binary formats, operating-system loaders, dynamic linkers, virtual memory, and processor execution.Mastering ELF: From Bytes to Execution is a comprehensive, implementation-focused engineering reference to the Executable and Linkable Format (ELF), with a particular emphasis on ELF64 internals and low-level runtime behavior. Across 50 chapters, it follows the complete execution pipeline from raw binary structures and defensive parsing to kernel-space loading, dynamic symbol resolution, thread-local storage, exception unwinding, executable modification, and custom loader architecture.

Ready to take your infrastructure skills to the next level? Mastering Pulumi shows you how to build, deploy and manage real-world infrastructure across multiple clouds using familiar programming languages. From your first project to complex enterprise platforms, discover practical techniques and proven patterns to make infrastructure more reliable, secure and easier to maintain.

Ready to take Supabase beyond the basics? Learn how to build real-world applications from the ground up, with secure database design, multi-tenant architecture and performance tuning at every stage. Packed with practical code and lessons from production engineering, this book shows you how to build applications that are ready for the demands of the real world.

This is a hands-on, code-first book. Every example is real, tested, and runs against a local model with no cloud key required, except where a capability genuinely needs one. You get working Maven projects, not snippets, and a clear-eyed account of each stack's strengths, gaps, and surprises. The full source code is on GitHub under an open-source license What you'll learn:Build a working AI service in three stacks and grade them with one shared testGround answers in your own documents with RAG, and tune what retrieval returnsGive a model memory and tools, and reach external systems over the Model Context ProtocolAdd vision and audio, structured output, production observability, and securityGo from assistants to agents, and see where the JVM's agent story is headingWho it's for: Java developers and architects choosing an AI stack, or already committed to one and curious what the alternatives do differently. Comfort with modern Java and either Spring Boot or Quarkus is all you need. No machine-learning background required.

Ready to move beyond AI prototypes? Learn how to build agents that reason, plan, use tools and tackle real-world tasks. From core concepts to production-ready architectures, this practical guide covers the code, design decisions and engineering challenges you need to build reliable, secure and scalable agentic systems.

Grokking LLMs makes the inner workings of large language models easier to understand, from the ideas that power them to how they learn and generate text. Build your knowledge step by step and discover what’s happening beneath the surface of today’s most exciting AI technology.

What if you could engineer a business the way you engineer software?Digital-First Business presents a systematic approach to business design based on software engineering principles. Learn how to structure operations, define business domains, integrate workflows, and build organizations that are observable, automatable, and designed to evolve.A framework for founders, executives, engineers, and anyone building the next generation of businesses.

Build AI agents that wake up, detect problems, and take action without waiting for a prompt. Through illustrated architectures, six practical use cases, and a runnable Python project, learn how heartbeat systems turn autonomous behavior into reliable automation and how to build a business around it.

Agents that plan, act and recover: the harness around the model. Tools, plans, checks, state, approvals and memory, drawn and built in Python.

Ready to build GIS applications that go beyond basic maps? This practical guide takes you from core spatial concepts to production-ready geospatial systems, with hands-on projects covering web mapping, spatial databases, real-time tracking and enterprise analytics. Learn the tools, techniques and engineering practices needed to turn geospatial ideas into reliable applications.

Build production-ready web applications in Rust without getting lost in architectural guesswork. Rust off Rails brings together proven conventions, a carefully chosen tech stack and hands-on guidance to take you from a blank project to a secure, scalable application. Learn by building Railboard and keep a practical reference close at hand long after the project is done.

AI can write code, create images and make decisions, but do you really understand what happens behind the scenes? This book cuts through the hype to explore how AI works, where it falls short and what it takes to build reliable systems. If you want to understand AI beyond the chat window, start with the code.

Building AI agents is one thing. Making them reliable in production is another. This book explores why agents fail and how to design systems that hold up under real-world conditions. From architecture and engineering patterns to evaluation and operations, it gives technical leaders the tools to build agents they can trust.

What can you learn from hardware that comes with no documentation, missing schematics or a protocol nobody has explained? This book explores practical methods for uncovering how electronic systems work, combining hands-on investigation, software analysis and AI to turn unknown hardware into something you can understand, analyze and rebuild.