Artificial Intelligence

In this groundbreaking guide, Dr. Mohammed Hamed Ahmed Soliman — engineer, professor, and industry consultant — takes you on a practical journey into the world of AI-driven maintenance. You’ll discover how to transform operational data into actionable intelligence, reduce unplanned failures, extend equipment life, and maximize return on assets.

Construa um AI agent completo do zero — de uma chamada simples à API até um sistema multi-agente em produção com memória, planejamento, RAG, segurança e deploy. 15 capítulos, um projeto real, código Python completo.

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.

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.

AI doesn’t fail loudly. It generates code that looks correct and compiles anyway. This book shows you how to make AI dependable by building the context and guardrails that keep your team shipping instead of debugging.

Geopolitik ist zu langsam. Entdecken Sie, wie die Naciro Engine KI nutzt, um den Puls der Nationen in Echtzeit zu messen – mit einer 15-minütigen Rekalibrierung von globaler Wahrheit und Macht. Check the live data on https://nationfiles.com

A concentrated scientific overview of the NationFiles framework. This monograph details the methodology and application of AI-driven real-time stability indexing for research and peer review. Check the live data on https://nationfiles.com

Discover the LPU architecture. This note details the specialized inference stack used for sub-50 ms latency and deterministic data embedding within the Naciro Intelligence Engine. Check the live data on https://nationfiles.com

Experience the speed of modern geopolitics. This overview details the NFSI’s 15-minute recalibration cycle and the global data infrastructure powering the NationFiles framework. Check the live data on https://nationfiles.com

The official technical audit for the NFSI. Access the complete formulas, weight matrices, and validation logic behind the NationFiles Stability Index to ensure total transparency. Check the live data on https://nationfiles.com

Discover the logical heart of the NFSI. This paper explains the 3-stage pipeline used to transform heterogeneous OSINT signals into a traceable and auditable geopolitical stability index. Check the live data on https://nationfiles.com

A deep dive into the NationFiles Stability Index (NFSI). Discover how 115+ real-time indicators and the Naciro Intelligence Engine redefine geopolitical risk analysis through transparent, rule-based 15-minute recalibration. Check the live data on https://nationfiles.com

Written by renowned lean expert and systems engineer Mohammed Hamed Ahmed Soliman, this book bridges the gap between frontline operations and cutting-edge AI tools. Packed with real-world examples, no-code platforms, and powerful frameworks, it shows how smart teams are streamlining processes, boosting productivity, and accelerating innovation—using tools they already have.