A Structural Approach to Mitigating Relay-Discontinuity in Human–AI Interaction: The Cognitive Anchoring Node (CAN) Framework

Human-Ai interaction (HAI) is inherently constrained by sesson-based discontinuities, leading to what has been termed 'relay discontinuity.' This paper introduces the Cognitive Anchoring Node (CAN) framework and the Mutual Contextual Optimization (MCO) mechanism to stabilize cognitive trajectories. Unlike passive memory systems, CAN provides an active structural environment to cognitive anchoring based on the user's sovereign intent. We provide a structural model and quantitative metrics, including Context Retention Rate (CRR), Semantic Coherence Index (SCI), and Insight Emergence Frequency (IEF), to establish a methodology for sustained knowledge construction in HAI.