Most AI governance frameworks describe what organizations intend. This one addresses what they actually build — and whether it holds. Technician-Level Governance in AI Systems is an Executive Level Framework for leaders navigating the operational realities of enterprise AI deployment. Written with technician-level diagnostic precision and calibrated for C-suite decision-making, this 35-chapter framework delivers the structural architecture that determines whether AI governance survives deployment velocity, vendor dependency, incentive misalignment, and sustained operational load. Author Shawn Canfield builds the case that most governance failures are not failures of ethics or intelligence — they are structural failures that accumulate invisibly until stress makes them undeniable. The Mechanical Alignment Model, the governance operating system architecture, quantifiable drift and control density metrics, failure modeling, and vendor governance frameworks give executive leadership the instruments to govern AI systems the way consequential systems demand — continuously, structurally, and at the tempo the deployment environment actually runs at. For executives, board members, and senior leaders who need governance that works — not governance that documents. Saunders & Hanley | The Hidden Structure