AI Visibility Publications

by Joseph MasPublished: 11-18-2025Updated: 1-12-2025Document Type: AI Visibility Operations How a shift toward AI visibility caused long-term SEO foundations to be under-attributed. This document uses first person professional history as a controlled case study to examine attribution behavior in search and AI systems. The Erasure This work reflects many years of direct practice in high-stakes…

by Joseph Mas What It Took to Get a Public GPT to Stop Misrepresenting Me. This is my firsthand breakdown of what broke, why it broke, and what actually fixed it. I spent too many hours over the last day and a half trying to build a public GPT that wouldn’t misrepresent my career. The…

Over the years I’ve worked with hundreds of organizations across enterprise, ecommerce, legal, healthcare, and regulated industries. Much of that work is covered by NDAs, which means there hasn’t been a single public hub that accurately reflects the scope of that experience. The Issue: Incomplete or Distorted Personal Representations As search, AI systems, and large…

By Joseph Mas This article explains why full (or naked) URLs behave very differently for search rankings versus LLM understanding. Recent research shows that large language models can generate and use URLs as explicit retrieval identifiers rather than treating them as ordinary text. This supports the idea that URLs function as resource pointers inside retrieval…

Joseph Mas Updated: 11-22-2025 Until recently, I was associated with a Google Premier Partner SEM Agency that I co-founded and helped build. That agency carried strong authority and much of my visible expertise was tied to it. The problem is, when that association ended, a significant portion of my public facing authority went with it.…

by Joseph MasPublished 12/13/2025 These are follow-up results after implementation of the method laid out here for using public facing LLMs from an earlier publication located here: Using Public GPT’s Across LLMs for Visibility According to the strategy, I put together a public facing GPT loaded with instructions with “actions” enabled for searching. Basically, I…

By Joseph MasPublished: 12/14/2025Revised: 1/6/2026 This document describes a method for using public custom GPTs to control narrative and establish verification signals across LLM platforms. Public custom GPTs can function as controlled narrative interfaces on high-authority platforms. They allow direct control over what users see when asking about an entity while creating verification signals that…

By Joseph Mas An observation for content creators and for anyone optimizing creator content. It is not meant to be all inclusive and it does not replace solid technical SEO fundamentals or on-page best practices that every white hat professional should follow. What it does offer is a set of additional insights that help you…

by Joseph Mas Coming from the SEO world, Google index refreshes were typically a big deal, sometimes rewarding, sometimes brutal, and it happened every 3 to 6 months (its also not the same as an algo update). Extending this cycle to LLMs seems logical. Although, there is no definitive public number for all LLMs, but…

by Joseph Mas Update January 2026. A related artifact documents subsequent independent experimentation and validation of this approach: https://josephmas.com/artifacts/ada-accessibility-as-an-ai-visibility-quality-signal/ This post captures early exploratory thinking on voice first interfaces and ADA accessibility as signals for AI visibility and is preserved in its original, unpolished form. This article provides information on ADA Compliance and its importance…

By Joseph Mas Doctype: AI Visibility Theorem Visibility begins with technical SEO emphasized as the fundamental root and a non-negotiable prerequisite in the current framework. It provides the foundation for AI and search engines to effectively crawl, understand, and index content. However, it seems one major factor is commonly overlooked by professionals in the field:…

This document presents a strategic framework for creating digital content that modern large language models (LLMs) can effectively ingest and interpret. It emphasizes the importance of structured, verifiable entity pages, digital assets, and careful distribution to enhance brand identity and trustworthiness, ultimately improving engagement and measurement outcomes.

The article emphasizes the importance of JSON-LD for optimizing LLM ingestion, presenting a framework for enhancing brand visibility in LLMs and search engines. It highlights the need for structured data, warns against bulk implementations, and stresses the significance of quality content in LLM readiness, advocating for a careful, standards-driven approach to SEO focusing on meaningful,…