Books

Error-proofing is no longer just about simple jigs and sensors. In the era of Industry 4.0, factories demand smarter, AI-powered approaches to achieve zero defects at the source.

Stop clicking. Start engineering. In a world of cloud-native infrastructure and rapidly evolving threats, security shouldn't be a "configuration task" hidden inside a vendor’s UI. It should be first-class software. Detection-as-Code: The Architecture Blueprint is the definitive guide to removing the "Save" button from your security consoles and replacing it with a high-velocity, version-controlled, and AI-augmented defensive pipeline.

One viral sketch. Two futures at stake. A choice that could cost them everything.

One architect. One unbreakable spirit. A corporation built on silent exploitation. When Chunmun Singh fights back against the Parramatta Protocol, he ignites a war that will bring down an entire system of greed.

The chapter that grew into its own book: existential and universal restrictions, the correct VegetarianPizza pattern, and how OWL restrictions become EKA governance.

Code Is the Side Effect"Software engineers are not primarily code writers. We are clarity traders — and that hasn't changed."You've seen the demos. The AI builds a whole feature from a sentence. The agent writes tests, fixes the failing ones, opens the PR. It's remarkable.Then you come back three months later. The codebase is a tangle. Nobody knows why anything is the way it is. The agent that built it has no memory of what it decided or why. And every time you ask it to add something new, it breaks two things you didn't know were connected.This is the pattern that nobody talks about. AI coding tools make the easy parts of engineering dramatically easier. They leave the hard parts untouched — and they create new hard parts that didn't exist before.Ways of Working is the book for engineers who want to work with AI agents rather than be gradually replaced by them — who understand that the tools are genuinely powerful and genuinely limited, and want to build practices that get the most from each.What you will actually learnThe world model framework. Before an agent can build anything well, it needs to understand what it's building and why. This book teaches you to give agents what they need: a structured, queryable representation of your architecture, your component contracts, your behavior specifications, and your code patterns. No world model = no sustained agentic development.Intent documentation. The most expensive bug in agentic codebases is not a hallucination — it's a decision made without context. Why is this rule here? Why is this boundary where it is? Agents can't infer rationale from code. You have to write it down.Spec-Kit and formal specifications. GitHub's Spec-Kit brings machine-readable, traceable, CI-verified specifications to engineering teams. This book shows how to use it to turn requirements into agent inputs that are precise enough to generate correct implementations.Graph explainers. Tools like Graphify and Understand-Anything transform codebases and documents into queryable knowledge graphs — giving agents navigable context instead of flat text. This is the memory substrate that makes multi-agent systems reliable at scale.Agent architecture that holds. What makes an agent coherently itself? When do file-based agent systems break down and what replaces them? How does constraint-based coordination (borrowed from holocracy) solve the autonomy-coherence problem that has stumped AI researchers for decades?Claude Code, for real. A complete treatment of Claude Code's CLAUDE.md convention, permission model, hooks, and slash commands. Plus the oh-my-claudecode ecosystem: 15+ specialized agents, workflow orchestration patterns (autopilot, ralph, ultrawork), and the skills framework for team-specific automation.The AI-native organization. What genuine AI-native teams look like beneath the marketing. How to hire, structure, and lead them. What language-oriented programming and constrained natural language mean for the future of the human-code relationship.Who it's forEngineers who are past the "should I use AI?" question and into the "how do I use it without losing my engineering integrity?" question.Senior engineers. Engineering managers. Technical leaders. People who have noticed that the more they delegate to AI, the less certain they feel — and who want to understand why.From the AuthorI've been building production systems with AI agents for years. Not demos — systems that had to work reliably across months, maintain themselves as requirements changed, and produce outputs that engineers could understand and defend.That experience has made me skeptical in both directions.Skeptical of the "AI will do everything" vision — because I've watched too many AI-generated codebases collapse under the weight of accumulated misunderstanding.Equally skeptical of the "nothing fundamentally changed" position — because the engineers who treat AI coding tools as just faster autocomplete are making a category error they'll pay for in months of maintenance debt.Something genuinely new is happening. This book is my attempt to think about it clearly.

Il giudizio non si delega. Il perimetro entro cui l'agente si muove, la verifica che deve passare, la condizione che lo ferma: quelli sì. Come un Senior trasforma vent'anni di mestiere nei vincoli che governano un agente, e come decisioni, criteri e lezioni restano quando la sessione finisce: è l'amplificazione del titolo.

"What if building microservices was as simple as running a food court? Each stall does one thing perfectly—pizza, burgers, smoothies—no chaos, just collaboration. Some remember your order (stateful), others don’t (stateless). This book turns distributed systems from a nightmare into a well-oiled machine. Ready to serve up scalable, cloud-ready microservices in Python? Dive in!"

Stop guessing and start diagnosing. Master the essential circuits of the Starter, Alternator, and Wiper systems with this practical, step-by-step engineering guide. Built for those who demand precision and real-world results.

What if your team could stop problems the moment they begin — or even before? That’s the power of Andon, one of Toyota’s simplest and most powerful Lean tools.

Many companies chase lean tools—kanban, takt time, one-piece flow—but fail to grasp the deeper philosophy behind them. While Just-in-Time (JIT) gets most of the spotlight, it’s Jidoka—the second pillar of the Toyota Production System (TPS)—that makes quality truly sustainable.

What if agentic AI was less about hype and more about work you can actually inspect?OpenClaw and Hermes for Agentic AI is a practical field guide to building with local agents, memory, tools, sessions, cron jobs, and ACP bridges. It shows how to turn fuzzy ideas into reliable workflows with clear boundaries, real artifacts, and human review where it matters most.If you want a grounded look at how agent systems really operate, this book starts there.