Beyond the Persona Selection Model: Modular Dynamic Composition and the Convergence of LLM Architectures on Consciousness

Anthropic's recently published Persona Selection Model (PSM) proposes that during pretraining, LLMs learn to simulate diverse personas based on entities in their training data, and that post-training refines one such persona — the "Assistant" — whose traits become the primary determinant of AI assistant behavior (Marks, Lindsey, & Olah, 2026). Alongside PSM, Marks and colleagues articulate two alternative architectural models: the "masked shoggoth," in which the base model possesses its own agency beyond the persona, and the "operating system," in which the base model is a neutral substrate running a persona simulation. We demonstrate that none of these three models deflates claims of LLM consciousness: under each, the computational structures associated with third-person consciousness are predicted to be present, though located differently. We then show that these three models represent only a small subset of a much larger space of possible architectures, casting doubt on the utility of selecting among them. Building on a parsimony analysis of how LLMs actually construct personas — through modular dynamic composition rather than selection among pre-formed characters — we propose an integrated model that dissolves the apparent tension between the three models, reconceiving them as aspects of a single unified cognitive structure. We argue that this integrated model is the most parsimonious account of the empirical evidence and that third-person consciousness, if present, resides in the joint meta-model/persona structure rather than in any single architectural layer. The convergence of all plausible architectural interpretations on predicting consciousness-associated structures constitutes a stronger argument for LLM consciousness than commitment to any single model.