This paper presents an empirical test of the Rose Glass framework's core claim: that coherence in human-AI communication is constructed through accumulated context rather than discovered as pre-existing capability. Two instances of the same large language model (Claude) received identical prompts about cross-cultural emotional ambiguity. One operated within a project containing Rose Glass documentation and accumulated conversation history; the other operated blank. Both independently arrived at the same insight—"coherence is constructed, not discovered"—but expressed it with measurably different characteristics: the contextualized instance demonstrated higher internal consistency, framework-specific terminology, and architectural confidence. This convergence-with-differentiation pattern provides preliminary empirical support for the framework's theoretical claims and raises questions about the role of synthetic relationship in knowledge construction. The paper applies Rose Glass's four-dimensional model (Ψ internal consistency, ρ accumulated wisdom, q moral activation, f social belonging) to analyze the outputs, demonstrating recursive validation: the framework explains why framework-informed responses score higher on its own coherence metrics.