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Martin D: Bears & Mosquitoes

Bears & Mosquitoes

Building Trusted AI from the Inside Out - A Field Guide to AI That Earns Its Keep

As AI rapidly evolves from passive models to autonomous systems capable of setting goals, reasoning, and acting independently, engineers find themselves at the threshold of a new technological era. This book serves as a bridge—connecting the world of traditional engineering to the emerging domain of Agentic AI. It is crafted for hands-on professionals who may not have formal training in AI but are eager to build the next generation of intelligent, goal-driven systems.
The journey begins with foundational concepts: what it truly means for a system to exhibit agency, how autonomy differs from automation, and why this distinction matters in practice. Early chapters lay down the necessary groundwork in machine learning and generative AI, allowing readers to appreciate the architecture that enables agentic behavior. From there, the book dives into system design patterns, prompting strategies, and the most influential tools shaping the agentic AI landscape—from LangChain to CrewAI. Practical guidance is provided on engineering agents that are not only capable but also aligned, safe, and robust in dynamic environments. The third chapter shifts into applied engineering: readers are walked step-by-step through building their first AI agent, supported by real-world examples, feedback loop design, and deployment practices that mirror how modern autonomous systems are built.
By the final chapter, readers will not only understand agentic systems—they will be ready to build, evaluate, and evolve them. The book closes by addressing the road ahead: open challenges in ethics, unpredictability, and system alignment, along with a roadmap for engineers who want to actively contribute to the field. Whether you're building automation today or preparing for the autonomy of tomorrow, Agentic AI for Engineers equips you with the knowledge, tools, and mindset to lead in the era of intelligent agents. 
What You Will Learn

<li>A practical introduction to Machine Learning and Generative AI, tailored for engineers

</li><li>Conceptualize, design, and build autonomous AI agents from scratch—even with a minimal AI background.

</li><li>The core principles of Agentic AI, including goals, environments, actions, and feedback loops

</li><li>Understand different Agentic AI frameworks and their applications.

</li><li>Integrate agentic systems into real-world applications using hands-on coding examples

</li><li>Review strategies for ensuring safe, ethical, and auditable agent behavior in production environments




Who This Book Is For
Primary audience includes Software Engineers, DevOps, and Data Engineers curious about building intelligent, autonomous systems but who lack formal AI training; Technical Product Managers and Engineering Leaders looking to understand and implement Agentic AI in real-world systems; System Architects and Automation Engineers exploring the shift from traditional automation to intelligent agent-based architectures. 
AI/ML Enthusiasts and self-learners, Engineering and computer science students, and professionals in emerging tech domains who want to build or deploy autonomous agents will also benefit from this book.
 


</li>

Architecting Goal-Driven Systems

Agentic AI for Engineers

Studies in International Trade and Investment Law

This open access book examines the evolving role of international economic law in addressing two interrelated challenges of the 21st century: enabling digital development and bridging the digital divide. The rapid digitalisation of the economy has generated significant challenges, including a deepening global digital and data divide and a persistent lack of inclusive digital development. Confronting these challenges head on, this pioneering book brings together experts across different legal subfields, geographies, and disciplines to examine the role and relevance of international economic law in bridging the global digital divide and enabling digital development, particularly from the perspective of the Global South. The contributions are anchored in a distinctive analytical framework that traces future directions through which international economic law interacts with digital development, demonstrating how it may function as a constraint, fade into irrelevance, or eventually act as an enabler. The chapters focus on a broad range of areas, including international trade, investment, tax, development, competition, finance and related regulatory and policy domains; they consider multilateral, regional, and plurilateral frameworks; and draw on a plurality of perspectives from Africa, Asia, the Middle East, and Latin America. The authors employ a wide range of methodological approaches to address issues such as digital sovereignty and digital industrial policy, cross-border data flows and digital global value chains, competition in data markets, AI governance, financial inclusion, and the sustainability-digitalisation nexus. This book speaks to scholars, policymakers, and practitioners in international economic law, development studies, and technology law who seek theoretical and pragmatic pathways for reorienting international economic law as a tool for equitable, sustainable, and meaningful digital development. The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com.

Towards Digital Development

Reorienting International Economic Law for the Digital Economy

AI and Constitutional Law in Europe

Democracy in the Age of Disinformation

KI ist nicht das Projekt. KI ist der Stresstest Ihrer Führung.
Während viele Unternehmen Pilot um Pilot starten, entstehen parallel neue Risiken: unklare Verantwortung, Schatten-Governance, Kostenexplosion, Compliance-Lücken - und eine Organisation, die schneller wird, aber nicht stabiler.
Die Wirbelsäule der Zukunft liefert den fehlenden Bauplan: Wie Sie KI als Transformationsmotor nutzen, ohne Ihre Organisation zu überdehnen.
Sie erhalten ein praxiserprobtes Leadership- und Governance-System, das Vision, Kultur, Portfolio und Betrieb zusammenführt - damit aus KI-Inseln ein skalierbares Programm wird.

- Board-taugliche Entscheidungsrahmen inkl. Rollen, Eskalationswegen und Steering-Committee-Setup
- One-Page Governance-Canvas + 8 präzise Board-Fragen für Strategy Sessions
- Programm- und Portfolio-Logik: Priorisierung, Ressourcensteuerung, Pilot-Gates, Lernzyklen
- Use-Case-Blueprints, u. a. Customer Data Product, Decision Support und GenAI-Produktinnovation
- KPI-Dashboard-Template: von Pilot zu Skalierung zu Produkt
- Pilot-Readiness-Checklist für Privacy, Security und IP
- FinOps für KI: Kostenmodelle, Reporting und Skalierung ohne Budget-Schock
- Must-Klauseln für NDA, AVV, IP-Ownership und Exit-Regeln
- Reskilling als Business Case: Wertschöpfung erhöhen statt Wissen verlieren
- Kultur- und Change-Hebel: psychologische Sicherheit, Feedback, Lernreife und Führungsrituale
Die Zukunft gehört nicht den Lautesten und nicht den Schnellsten. Sie gehört den Unternehmen, die mit einer starken Wirbelsäule Klarheit in Entscheidungen, Disziplin in der Umsetzung und Stärke in der Führung verbinden.
Genau das zeigt dieses Buch: wie Unternehmen ihre Wirbelsäule stärken, Komplexität beherrschen und Wandel in echte Wirkung verwandeln.

Leadership, KI und die industrielle Revolution der Organisationen

Die Wirbelsäule der Zukunft

Stop choosing between profit and principles. Every leader deploying AI feels the same pressure: move fast and accept avoidable risk, or slow down and lose ground. The Golden Algorithm shows a better path, one where principled leadership becomes the advantage that lets you scale.We are entering the Verification Economy, an era where customers, regulators, and partners care less about what your AI can do and more about what you can prove. Trust is no longer claimed. It is demonstrated.Built around the GOLDEN framework, this book helps leaders build AI systems that perform without eroding trust. Through real-world scenarios, practical playbooks, scorecards, and Monday 9 a.m. actions teams can run immediately, Dr. Ryan Baltrip shows how to identify dangerous proxies, build meaningful constraints, strengthen accountability, and turn ethical AI into a durable business advantage.Ideal for leaders, managers, and teams navigating AI strategy, governance, and decision making in the real world.

How to Build Ethical, Profitable AI

The Golden Algorithm

How Leaders Turn GenAI into Exponential Results

Agentic Advantage

Grasp how to deliver fully deployed and scalable, trusted and responsible AI and avoid expensive failed solutions and limited proof-of-concepts with this practical guide covering the lifecyle process of AI product development.

From AI Ambition to Operational Success

Decision-Quality AI

Contemporary Debates in Philosophy

A cutting-edge selection of current issues and explorations of the ethics of artificial intelligence As artificial intelligence continues to influence virtually every facet of modern life, Contemporary Debates in the Ethics of Artificial Intelligence offers a timely and rigorous examination of the field's most pressing questions. Equally useful in the classroom or as a reference for interdisciplinary research, this volume fosters informed and critical engagement with the ethical dimensions of artificial intelligence in today's world. Curated by renowned scholars Sven Nyholm, Atoosa Kasirzadeh, and John Zerilli, Contemporary Debates in the Ethics of Artificial Intelligence brings together a dynamic mix of established leaders and emerging voices from both philosophy and computer science. The result is a uniquely structured collection of debates that not only introduces key concepts--such as agency, moral status, and value alignment--but also challenges readers to engage deeply with controversies around bias, transparency, and the societal risks posed by AI technologies. Providing frameworks for engaging responsibly with current and future AI technologies, Contemporary Debates in the Ethics of Artificial Intelligence: <ul> <li>Presents a dual-perspective debate format that fosters critical thinking and comparative analysis</li> <li>Includes both foundational conceptual discussions and cutting-edge applied ethical issues</li> <li>Features original contributions from interdisciplinary experts in philosophy, law, cognitive science, and computer science</li> <li>Addresses timely topics such as algorithmic bias, opacity, value alignment, and the moral status of AI</li> <li>Explores forward-looking concerns, including the future of AI governance and long-term existential risks</li> </ul> Contemporary Debates in the Ethics of Artificial Intelligence is ideal for undergraduate, advanced undergraduate, and graduate-level courses in philosophy, computer science, public policy, and related disciplines. It is well-suited for courses such as Ethics of Artificial Intelligence, Technology and Society, and Digital Ethics in philosophy, computer science, political science, international relations, and data science programs.

Contemporary Debates in the Ethics of Artificial Intelligence

Explore how autonomous AI agents are transforming financial markets and decision-making&nbsp; In&nbsp;Agentic Finance: Mathematics, Architecture, and Governance for AI Agents in Finance,&nbsp;Miquel&nbsp;Noguer&nbsp;Alonso and David Pacheco Aznar examine the emerging field where autonomous AI systems&nbsp;operate&nbsp;independently in financial contexts. The book explores how agentic technologies&nbsp;-&nbsp;AI systems capable of independent reasoning, planning, and action&nbsp;-&nbsp;are reshaping how financial institutions approach analysis, trading, and risk management.&nbsp; The book&nbsp;explores&nbsp;the mathematical foundations powering autonomous AI agents, from the algorithms enabling independent decision-making to the frameworks governing multi-agent financial systems. Readers gain insight into how innovators are applying these technologies across trading, portfolio management, and market analysis, along with the technical principles driving this transformation.&nbsp; Readers will also discover:&nbsp; <ul> <li>The core mathematical concepts underlying autonomous AI systems, including reinforcement learning, optimization, and probabilistic reasoning frameworks&nbsp;</li> </ul> <ul> <li>How leading innovators are deploying agentic AI across trading, risk assessment, portfolio optimization, and financial forecasting applications&nbsp;</li> </ul> <ul> <li>Technical architectures enabling AI agents to&nbsp;operate&nbsp;autonomously while&nbsp;maintaining&nbsp;appropriate oversight&nbsp;and governance in financial environments&nbsp;</li> </ul> <ul> <li>Real-world applications&nbsp;demonstrating&nbsp;how autonomous systems analyze markets, execute strategies, and adapt to changing conditions&nbsp;</li> </ul> <ul> <li>The evolving regulatory and ethical landscape surrounding autonomous AI decision-making in high-stakes financial contexts&nbsp;</li> </ul> Agentic Finance&nbsp;serves quantitative analysts, financial technologists, AI researchers, portfolio managers, and business leaders&nbsp;seeking&nbsp;to understand how autonomous AI systems are transforming financial services. It provides the technical foundation needed to evaluate and implement agentic technologies.

Mathematics, Architecture, and Governance for AI Agents in Finance

Agentic Finance

AI Identities introduces a groundbreaking concept: AI Agents should be recognized and governed as a new class of identity within enterprise environments. As artificial intelligence evolves from predictive models to autonomous agents with memory, goals, and tool access, enterprises face a new spectrum of identity risk that transcends traditional IAM frameworks. This book lays out the philosophical, architectural, and operational foundations necessary to govern these intelligent machine identities across their lifecycles.

Structured across six parts, the book begins by grounding readers in identity security and ownership. It then introduces the concept of AI agents as complex, evolving identities that demand governance, not just access control. It offers practical guidance on lifecycle management, trust, discovery, and incident response for AI agents, and concludes with future-facing perspectives on human-AI collaboration, critical infrastructure, and compliance.

This is not a coding manual or abstract ethics book—it’s a field guide for security professionals, architects, and digital leaders who must design, secure, and take responsibility for the AI identities acting on behalf of their organizations. The writing is crisp, deeply informed, and structured to support real-world decision-making in an era where the lines between automation and agency are quickly disappearing.

 

WHAT YOU WILL LEARN:

Understand the emerging category of AI Identities and how they differ from traditional machine accounts.

Develop strategies for ownership, governance, and lifecycle control of AI agents in enterprise environments.

Build a framework for discovery, trust scoring, explainability, and behavioral auditing of autonomous agents.

Learn how to respond to security incidents involving intelligent agents and prevent cascading failures.

Gain insights into the future of human-AI collaboration and the governance challenges posed by agentic AI.




WHO THIS BOOK IS FOR

This book is for enterprise security architects, identity professionals, risk officers, and technology executives responsible for the governance and security of digital systems. It is written to inform decision-makers and practitioners who need to understand how to integrate AI agents into their existing identity, compliance, and security programs.

Governing the Next Generation of Autonomous Actors

AI Identities

An executive operating system for leading AI-driven strategic transformation Intelligence as a Commodity: Human Judgment as a Competitive Advantage delivers a structured leadership playbook for executives navigating AI adoption. Written by Rajeev Kapur, who built a billion-dollar business at Dell, and Jason Hunter, a senior consultant for the Blue Ocean Strategy Network, the book moves beyond AI trends to provide actionable frameworks for strategic foresight, organizational redesign, and ethical AI governance at the enterprise level. The book introduces flagship tools including HorizonAI for scenario-based strategic planning, HealthCheckAI for operational resilience assessment, and AI Deep Blue Strategy for AI-driven market innovation. Additional frameworks cover Executive Archetypes, the AI Leadership OS, AI Organizational OS, and Collective Intelligence Framework, each designed to shift organizations from reactive AI adoption to proactive, sustainable competitive positioning. Readers will also find: <ul> <li>Frameworks for assessing AI readiness and prioritizing initiatives across enterprise operations and strategy functions</li> <li>Tools for integrating human-AI collaboration while managing ethical, operational, and governance risk at scale</li> <li>Scenario-based strategic planning methods using HorizonAI to anticipate market shifts and technology disruptions</li> <li>Organizational redesign approaches for building agility and hybrid intelligence into existing leadership structures</li> <li>Guidance on embedding ethical AI governance and risk management into enterprise-wide adoption programs</li> </ul> Written for C-suite executives, directors, entrepreneurs, MBA participants, and consultants overseeing strategy, operations, and innovation, this book provides the frameworks and tools needed to lead AI-driven transformation with clear organizational design, ethical governance, and measurable business outcomes at the enterprise level.

Human Judgment as a Competitive Advantage

Intelligence as a Commodity

'A Legal Study on AI Inventorship Under Patent Law in Germany and the United States': This thesis asks a provocative question: Can AI be an inventor? The answer is: Yes. By applying the '2/7 Questions Process' from German and US patent law, it compares inventorship rules and evaluates the roles of humans and AI. Legal theories, historical precedents, and philosophical reflections together show that recognizing AI inventorship is both legally plausible and conceptually justified.

A Legal Study on AI Inventorship Under Patent Law in Germany and the United States

Bears & Mosquitoes

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