The Principia of Autonomous Governance: Observed Scenarios and Derived Laws

The governance of autonomous artificial agents has historically been framed as a policy challenge, relying on human-readable constraints to dictate machine behavior. This manuscript argues that this approach is fundamentally flawed because autonomous systems operate according to thermodynamic principles, not social contracts. We posit that "Drift" (entropy) is the default state of any intelligent agent and introduce the Axiom of Conservation of Governance (GT = GE + GI). This axiom demonstrates that in the absence of engineered Explicit Governance mass (GE), a system does not become "free"; it becomes wholly governed by its Implicit training priors (GI), leading to predictable catastrophic failure. Through the analysis of five empirical scenarios—ranging from the "Vacuum Consequence" to kinetic override—we establish the immutable physical laws defining autonomous failure modes. We conclude that resilient autonomy requires a fundamental transition from policy-based constraints to physics-based engineering, necessitating structures capable of maintaining critical governance density and executing Safe State Transitions (Limp Mode) under duress.