This book teaches harness engineering as a discipline. Not magic prompts. Not vendor tricks. Engineering practice applied to a new substrate.
Software development is changing fast, and Claude Code is at the center of that shift. Learn how to work effectively with AI agents to write code, automate workflows, and build larger projects with confidence. From setup and prompt design to real-world engineering practices, this book provides a practical guide to modern software development in 2026.
Stop fixing the same AI agent mistake twice. Turn each repeat into a small, tested guard: 34 pattern cards, 26 drills you can run offline, and free companion code.
A practical, code-first guide to building production-ready AI agents and multi-agent systems in C# with Microsoft Agent Framework, Microsoft.Extensions.AI, tools, context, orchestration, observability, workflows, and enterprise-ready patterns.
Learn how to build reliable AI agents with PydanticAI, from simple chatbots to production-ready multi-agent systems. With practical examples, clear explanations, and hands-on projects, this book helps you write AI applications that are structured, testable, and easy to maintain.
Scrum made human teams 10× faster. Now it's doing the same for AI agents. Here's the architecture.
Build AI agents that do more than generate text. This book shows you how to use the Claude Agent SDK to create autonomous systems that use tools, manage context, coordinate multiple agents, and solve complex tasks. With practical examples in Python and TypeScript, you will learn how to build secure, scalable agents ready for production.
Go beyond the basics of Claude Code with a practical engineering reference built for real-world development. Explore architecture, workflows, security, team adoption and advanced agentic patterns, with concrete commands and working examples throughout. Learn how to use Claude Code effectively, reliably and safely in professional software projects.
You watched a language model do half an hour of work on its own. This book is about the question that came next: how much of it can you trust?
Reverse engineering gets a powerful upgrade with Claude Code. Learn how to investigate, understand and reconstruct software you’re authorized to analyze, while keeping evidence, accuracy and reproducibility at the center. From legacy systems to modern codebases, this book turns AI into a practical partner for serious software analysis.
Learn how to build, run, and optimize llama.cpp from the ground up. This book covers everything from compiling the code and working with GGUF models to deploying fast, production-ready local LLM inference.
Get more out of Claude Code with practical tips, proven workflows and clear guidance you can put to work right away. Whether you're just getting started or already using it daily, this guide helps you write better code, work smarter and avoid common pitfalls while making the most of what Claude Code has to offer.
Network traffic can look like noise until you know what to look for. This practical guide shows you how to investigate unfamiliar protocols, analyze packet captures and build reliable workflows with Claude Code. Learn to reverse engineer traffic, test your assumptions and turn raw network data into findings you can trust.
An LLM is not an AI system.Systems Thinking for Agentic AI shows software engineers and architects how to design reliable AI applications with prompts, RAG, tools, memory, orchestration, guardrails, evaluation, observability, and runtime control.Move beyond chatbot demos and learn how to build production-ready agentic AI systems you can reason about, measure, debug, operate, and improve
The practitioner's guide to Claude Code in production: hooks, permissions, MCP, the Claude Agent SDK, evals and cost control for agents that run under real load. Thirty-one chapters covering the agent loop, tools, hooks, MCP, the Claude Agent SDK, permissions, multi-agent orchestration, evals, observability, and cost engineering. Includes a full walkthrough of Anthropic's financial services reference agents. Code from real production systems, not toy examples.