OPERATIONAL SHAPES ACROSS LIFE, AI, AND ALGORITHMS Scientific Realism, Artificial Life, Active Inference, Open-Ended Evolution, and the Experimental Limits of Operational Equivalence

Biological autonomy, embodied cognition, open-ended search, robotic self-modeling, Bayesian structure learning, and automated experimentation offer mature mechanisms for generating and revising the conditions of action and inquiry. Consequently, the propositions that organism–environment boundaries are relational, that models may change, or that objective functions can impede novelty do not independently distinguish operational-shape realism. This article reconstructs the strongest relevant achievements and subjects previously reported P/A results to a deliberately asymmetric evidential audit: peer-reviewed external demonstrations are compared with reported simulator outputs, archived manuscripts, and their stated reproduction limits, rather than treated as equivalent evidence. An operational-shape description is specified as a bounded, revisable observational and intervention contract, and operational equivalence is expressed relative to accessible interventions, observables, histories, resources, and statistical resolution. We distinguish ontological independence, experimental detectability, and comparative non-redundancy; none implies the others. The extant P/A record supports limited methodological claims and informative negative findings, not superiority over contemporary active inference, quality-diversity evolution, adaptive robotics, or autonomous science. We formulate strong, equal-rights experiments and pre-registered withdrawal criteria. The resulting contribution is a stringent method for locating when explanatory distinctions matter, expire, or remain undecidable—not a claim that life, embodiment, or algorithmic reconfiguration were first discovered by this programme. Keywords: operational-shape realism; Xenoscience; scientific realism; artificial life; active inference; novelty search; quality diversity; operational equivalence; autonomous science; model revision A robot loses a limb, revises its self-model, and continues walking. An evolutionary system abandons a misleading objective and discovers behaviours inaccessible to local fitness improvement. A scientific machine formulates hypotheses and executes physical tests. An inference engine selects actions to distinguish competing world-model structures. These achievements are not hypothetical illustrations awaiting a philosophy of operations: they are established research contributions (Bongard et al., 2006; Lehman and Stanley, 2011; King et al., 2009; Friston et al., 2026). They change the obligations of any philosophical theory that describes itself as concerned with the emergence or revision of operative possibilities. The motivating question is not why a world contains bodies or algorithms. It is why particular descriptions of a world—organism, environment, agent, affordance, fitness landscape, state space, or scientific apparatus—should be privileged outside the interval in which they demonstrably do explanatory work. A research tradition is permitted to begin with life when its target is biological sense-making; it is not thereby committed to a universal thesis that life produces physical reality. Critique becomes legitimate only when such a priority is asserted or silently smuggled into an inference. This paper therefore rejects a generic anti-embodiment polemic. It instead compares the strongest completed results with what operational-shape realism can actually show. Three distinct claims must not be conflated. Ontological independence says that a material process need not depend for its occurrence on the observational concepts used to identify it. Epistemic access asks which discriminations and records make the process knowable. Comparative non-redundancy asks whether adding a proposed model or vocabulary changes prospective predictions, interventions, control, or the scope of justified ignorance when matched against a capable competitor. The first does not entail the third. That logical gap organises the study.