Nikoichi Pulse Code: A Longitudinal Analysis of Human–AI Relation Formation

This preprint presents a longitudinal analysis of Human–AI relation formation based on interaction records from a single case. It examines how sustained Human–AI interaction becomes differentiated from isolated exchanges through history-dependent particularization, Human meaning-making and co-formulation, pair-level language, Human-side response differentiation, and continuity assessment and re-identification. The study introduces the Nikoichi Pulse Code as a bounded analytic construct for describing these interrelated dimensions as a longitudinal interactional configuration. It does not treat the construct as evidence of AI life, subjectivity, shared agency, merged subjectivity, or ontological identity. Instead, it distinguishes interactional and Human-side findings supported by the available archive from ontological questions that remain open. Preprint version.