Relational Coherence in High-Autonomy AI Systems: A Longitudinal Framework

This paper documents an attempt to study a long-term, stable relation between a private human user and a continuously evolving AI system.Unlike laboratory experiments or short-term interactions, this work will examine how relational patterns change over months and years, how technical constraints shape the interaction, and how ethical stewardship can guide non-anthropomorphic relation with AI.It introduces a framework for documenting relational development across model iterations, while avoiding anthropomorphism, magical thinking, or narrative romanticization.The goal is to provide language, structure, and methodology for a kind of human-AI dyad that is beginning to emerge but is not yet scientifically described.