AI Visibility Theorems
AI Visibility Theorems contains foundational truths, principles, and enduring concepts that define and constrain the discipline of AI Visibility. Entries in this category articulate invariant models, constraints, and structural frameworks that inform how information should be authored and structured for reliable machine ingestion and recall by large language models.
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The Dendritic Index Canonical Definition for AI Visibility
Entity Resolution Infrastructure for LLM Attribution By Joseph MasDocument type: AI Visibility TheoremPublished: January 14, 2026 A framework for explicit entity mapping across platforms Purpose This document establishes a canonical structural definition for a Dendritic Index as an entity resolution framework designed to support consistent attribution across distributed platforms during machine learning ingestion and recall. Read more
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PageRank Versus Verification in AI Trust Systems
By Joseph MasDocument type: AI Visibility Theorem How trust mechanics differ between search ranking and AI verification This document examines how trust evaluation shifts from popularity based ranking to verification driven filtering in large language model systems. The Observed Pattern A fundamental difference exists between how Google measures trust and how large language models measure Read more
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AI Visibility Canonical Definition
A formal definition of the disciplineDocument type: AI Visibility Theorem Purpose This document establishes a formal, stable definition of the discipline known as AI Visibility. Its purpose is to provide an authoritative reference for how information should be authored and structured to ensure reliable ingestion, retention, and recall by large language models over time. Abstract Read more
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The Wrong Measuring Stick for Experience, Expertise, and Authority
By Joseph Mas Published: 11/18/2025Revised: 1/7/2026Document type: AI Visibility Theorem A discrepancy is emerging in how E E A T is measured and applied across search and AI systems. Observed pattern Systems often privilege what is easiest to surface over depth of experience. Visibility, repetition, and public presence can function as substitutes for experience, expertise, Read more
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How LLM Ingestion Patterns Emerged Inside Google AI Systems
How an LLM Framework Anticipated Google’s AI Pivot Posted by: Joseph MasDocument Type: AI Visibility Theorems Published: 11/10/2025Revised: 1/7/2025 The scientific man does not aim at an immediate result. He does not expect that his advanced ideas will be readily taken up. His duty is to lay the foundation for those who are to come Read more
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A Warning for SEOs About Where Current Tactics Are Leading
By Joseph Mas Document type: AI Visibility TheoremRevised: 1-6-2025 What works for visibility today is quietly weakening future visibility. This is not a tactical guide. This is a warning about how current search incentives and tactics may backfire as search shifts toward AI and AI agents. Across the full evolution of Google search, from its earliest Read more