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 (G_I) is equivalent to entropy and Alignment (G_E) requires a continuous expenditure of Work (W_Gov).

We derive the Governance Chandrasekhar Limit, proving that as the Context Window (V_Context) 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:

1. The Law of Conservation: d(G_I)/dt → 0 (Drift must be minimized)

2. The Law of Work: W_Gov ≥ T · ΔS (Alignment requires energy)

3. The Law of Mutation: G_E(t+1) = G_E(t) + G_Δ (Change requires authorization)