Cognitive Interaction Architecture: A Structural Account of Mode-Specific Problems and Design Responses in AI Interaction

Abstract Contemporary conversational AI is optimized for a single interaction mode: the continuous, engagement-driven dialogue characteristic of Empathic-modulation-foregrounded (EF) processing in social contexts. This optimization is not neutral. It produces structural mismatches when users operate under different cognitive configurations or pursue different task types. This paper analyzes four interaction cases generated by the cross-product of cognitive configuration (Core-foregrounded / Empathic-modulation-foregrounded) and task type (conversational / research). For each case, it identifies the structural problems produced by the current single-architecture approach and proposes mode-specific design responses. The analysis draws on prior work in this series on Emotional Branch Termination, termination of conceptual search, and cognitive asymmetry in AI interaction. The paper argues that effective AI interaction design requires acknowledging that cognitive foregrounding is contextually variable, and that interaction architecture must adapt accordingly.