Books

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.

Skip the black-box frameworks. Build a production-grade AI coding agent from scratch in pure Python—cloud or local, tested with pytest, under 700 lines.

The book covers every topic in the latest CISSP exam syllabus, organized in a format that makes it easy to drill down on specific exam domains and concepts at-a-glance, making it an essential exam resource for anyone who aims to prepare for the exam without wasting time or money.

A complete foundation for Statistics, also serving as a foundation for Data Science. Leanpub revenue supports OpenIntro (US-based nonprofit) so we can provide free desk copies to teachers interested in using OpenIntro Statistics in the classroom and expand the project to support free textbooks in other subjects. More resources: openintro.org.

A clear, illustrated guide to large language models, covering key concepts and practical applications. Ideal for projects, interviews, or personal learning.

The Few Simple Ideas Behind Every Object Oriented Pattern and Principle.

A practical guide to product engineering in an AI native era, where building shifts from manual construction to steering tools, editors, and agents. Product Engineering with AI covers platforms, agentic workflows, prompting, code quality, UX, and responsible practices for getting from prototype to production. 

Learn SysML v2 with the ultimate guide for all skill levels in MBSE. Authored by insiders, it's your key to unlocking the full potential of system modeling and a passport to mastering your MBSE.

Residuality Theory is a new way to think about the design of software systems that explains why we experience design the way we do, why certain things seem to work only sporadically, and why certain architects get it right so often regardless of which tools they use. A new, scientific approach is defined that fuses Software Engineering, Complexity Science, and Philosophy to produce an entirely new way to think about how to design software. The result is a theoretical base that allows architecture to finally become its own discipline.

Master language models through mathematics, illustrations, and code―and build your own from scratch!

With more than 1200 microcontrollers, STM32 is probably the most complete ARM Cortex-M platform on the market. This book aims to be the most complete guide around introducing the reader to this exciting MCU portfolio from ST Microelectronics and its official CubeHAL and STM32CubeIDE development environment.

This book covers every topic in the latest CISM exam syllabus, approaching topics from the ISACA perspective. It's 325+ pages organized in a format that makes it easy to drill down on specific exam domains and concepts at-a-glance, making it an essential exam resource for anyone who aims to prepare for the CISM exam without wasting time or money.

This book covers every topic in the latest CISA exam syllabus, approaching topics from the ISACA perspective. It's 400+ pages, organized in a format following the syllabus that makes it easy to drill down on specific exam domains and concepts at-a-glance, making it an essential exam resource for anyone who aims to prepare for the CISA exam without wasting time or money.

Logic is the most important branch of math to software engineering. Knowing logic opens up a vast world of development techniques, from everyday tricks of the trade to exotic tools for cracking impossible tasks. This book teaches the basics of logic and nine special logic-powered techniques: property testing, decision tables, constraint solving, and more. Over 50 exercises are provided to help readers master the material. No prior math background required!

Everything you really need to know in Machine Learning in a hundred pages.