Beyond the Token Limit:  Structural Coherence in Long-Context Human-AI Interaction through Load Minimization Theory (LMT)

Current AI systems face inherent difficulties in maintaining coherent long-context interactions due to token limits, context decay, and accumulating structural load. This paper explores how Load Minimization Theory (LMT) applied through gentle, low-ΔE human-AI interaction can help mitigate these challenges. By comparing interaction modes and examining model-specific synchronization and thread strategies, the author observes that mindful engagement and appropriate thread management can support greater structural coherence over time.