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On Trust and AI

A Blueprint for Confidence in the Intelligent Enterprise

by Alexander Feick

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INTRODUCTION

On Trust and AI

CHAPTER 1

Why This Book, Why Now

The Unreviewed ReportThe Current MomentWho This Book Is ForThe Executive DilemmaThe Dual MandateWhy This Book Is DifferentHow to Read This BookMy PerspectiveWhat's Next?

CHAPTER 2

Making Sense of the Language of AI

The Illusion of UnderstandingFrom Rules to Learning: A Quick PrimerGenerative AI: The Big Leap from Prediction to CreationVocabulary That Matters: Tokens, Models, AgentsRAG: Bridging Memory and KnowledgeAgentic Systems and Tool Use: From Single Shot to OrchestrationHype, Reality, and Workforce ImpactEssential AI VocabularyLevels of AI AdoptionSummary & Transition

CHAPTER 3

AI in the Business Lifecycle

Framing the JourneyHow AI Fits into the Business Project LifecycleDeciding When to Move AI Projects ForwardBridging to Threat Modelling and Trust

CHAPTER 4

AI Redefines Threat Modeling

Security FramingUnderstanding AI's Impact on AccountabilityAccountability Shifts from Human to AI: Trust BoundariesThe Shifting of Security ArchitectureA Jolt of Reality: Some AI-Specific ConcernsImplications Across Adoption LevelsBack to First Principles: Verify, don't just TrustGovernance Before Automation

CHAPTER 5

Runtime Attacks on AI

Setting the StakesA New Lens on SecurityPoisoned Documents – Trusted Content is now CodeCalendar Invite Hijack – Turning Ambient Data Streams into Command ChannelsCross‑Plugin Exploitation – Integration Privilege EscalationIn Closing

CHAPTER 6

AI Era Supply Chain Attacks

Model Poisoning – Backdoors in the Supply ChainModel Inversion & Data Extraction – Mining the AI's MemoryField Notes on Fragile FoundationsFrom Local Failures to Ecosystem Implications

CHAPTER 7

Revisiting Trust

Some Principles for Restoring Confidence in AI DecisionsScenario: Rebuilding Our AI Legal Assistant for TrustThe Three Pillars, OperationalizedInternal and External Trust — The Same Mechanics, Different UIThe Economics of Trust: Verification is the Value of an EnterprisePractical Tools to Ensure Confidence in AI DecisionsClosing: Vigilant Optimism

CHAPTER 8

The Architecture of Control

What an AI control plane is — and why you need oneWhere it lives (and what it touches)SOC Operations: From "Offloading Trust" to "Operating a Control Plane"Two Escalation PathsCore Component View of the Governance Control PlaneHow Control Loops Look in PracticeReviewing the Economics of TrustIntegration: Where the Control Plane LivesCost & Value: The Business Case in One SentenceBringing it all together

CHAPTER 9

The New Role of Humans

What Accountability Really Means (in Practice)Decision Tiers and Human RolesA Practical Example: The Software EngineerFundamentals for New Post-AI RolesRevisiting the Tungsten LessonScoping Human Roles to Carry the WeightCase in full: Cursor vs. Lovable under the Accountability LensAnti-patterns to AvoidAnti-Pattern Avoidance: Measuring What MattersHow this Builds on What We've Already DoneThe Quiet Discipline of Speed

CHAPTER 10

Shadow AI & Vibe Coded Applications

When the prototype becomes the systemWhat "vibe coding" Actually isConverting Shadow AI from Risk Nightmare to AI Production LineReview: Securing Your AI Production LineConclusion

CHAPTER 11

Glossary & Appendix

GlossaryAppendix: Quick Frameworks & ToolsOn AI and Authorship

CHAPTER 12

About The Author

About Alexander Feick

INTRODUCTION

On Trust and AI

Author Profile
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