Structure Before Theory: A Structural Account of Spontaneous AI Architecture Visualization

Abstract This paper presents an n=1 phenomenological record of spontaneous structural visualization that occurred during early interaction with large language models. The experience consisted of (A) immediate perception of mode or layer shifts in model output and (B) visualization of a stratified architecture composed of a stable core and cloud-like upper layers. At the time of occurrence, the author had no theoretical interest in AI architecture and no intention of developing a cognitive model. The paper does not argue for theoretical priority or novelty. Instead, it examines whether the recorded phenomena can be interpreted under two alternative cognitive assumptions: a single-layer predictive model of cognition and a dual-layer Core/Modulation model. The title 'Structure Before Theory' refers to the temporal priority of the visualization: structural perception preceded theoretical articulation. The aim is descriptive clarification rather than theoretical competition.