AI Visibility Downstream Metrics Segregation and Inclusion Theorem

This document establishes a formal boundary between upstream AI Visibility and downstream measurement systems used to observe large language model outputs. It classifies metrics such as brand mentions, citations, dashboards, scoring systems, and optimization tooling as downstream instrumentation that reflects surfaced access to learned representations without defining whether those representations exist. The theorem preserves AI Visibility as an upstream construct governing learning, compression, retention, and recall, while incorporating external marketplace definitions as dependent observational interpretations rather than competing definitions. It operates as a supporting boundary theorem to the canonical AI Visibility definition https://josephmas.com/ai-visibility-theorems/ai-visibility/