The Physics of Governance: Thermodynamic Limits of Autonomous Agents

The deployment of autonomous agents in high-stakes enterprise environments is currently constrained by a fundamental misunderstanding of alignment. We propose that "Governance" is not a policy layer but a thermodynamic function. By modeling the agent as a closed system subject to the Second Law of Thermodynamics, we demonstrate that "Drift" (GI) is equivalent to entropy and "Alignment" (GE) requires a continuous expenditure of work (WGov). We derive the Governance Chandrasekhar Limit, proving that as the Context Window (VContext) expands, the density of the system prompt must scale linearly to prevent identity collapse. We conclude by defining the "Three Laws of Governance Dynamics, " offering a mathematical framework for the stability of autonomous systems.