AI Visibility Operation: Aggregation Threshold Conditions

Aggregation Threshold Conditions for Entity Corpus Architecture This operation documents the corpus level signal conditions an entity must meet before LLM training ingestion produces stable entity representation. It addresses a condition that precedes page level optimization: whether sufficient structured, aligned corpus mass exists to cross the aggregation threshold at which a model forms a stable entity representation at all. Companion Operation This operation extends the AI Visibility Operation: Structuring Law Firm Pages for Shallow Pass LLM Ingestion and Compression Survival. That operation addresses page level structure. This operation addresses a separate and prior condition. Both must be met. Meeting one without the other may still produce insufficient signal. Four Corpus Level Conditions Canonical entity reference consistency across all pages. Offering terminology stability without drift across surfaces. Explicit entity declaration within the shallow pass zone. Elimination of promotional and unverifiable language from opening content. Framework Applies the Aggregation Threshold Theorem, Aggregation and Signal Formation Theorem, Semantic Stability and Drift Theorem, Authorship and Provenance Determinism Theorem, and Shallow Pass Budget Constraints findings. Part of the AI Visibility theorem set. Authored by Joseph Mas.