The Autonomous Incident Identification (AII) Doctrine: A Kinetic Framework for Empirical, Data-Centric Incident Classification

AI introduces the Autonomous Incident Identification (AII) Doctrine, a new, purely empirical framework designed to replace subjective, "gut-feel" incident classification methods. The core of this system is the monitoring of external-facing interfaces, called "Open Doorways," using a cost-effective, client-side "Sensor Grid" that records successful user access, defining failure as the absence of this expected signal (a Sensor Deviation). The AII system utilizes a Dual-Engine Physics Model (Kinetic Acceleration for "Flash Crashes" and Accumulator Mass for "Slow Bleeds") to calculate severity, shifting the focus from forensic analysis (the "Tornado Scale") to predictive telemetry (the "Hurricane Scale"). The system also employs a global DEFCON Calculator for Total Information Awareness (TIA) to manage alert suppression during widespread failures and institutes an automated, Zero-Touch Incident Lifecycle by quarantining incident data and auto-resolving once a "Return to Baseline" (RTB) is achieved.