Briefings
Briefings on AI structure, visibility, and discoverability. Practical insights from experiments on real websites.
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AI Discoverability
Context-Based Targeting: Event-Driven Uncertainty
When a storm or collapse hits before service intent forms, the strongest page is often the one that enters the disruption event and carries context forward.
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AI Discoverability
Outcome-Based Targeting
The strongest discoverability pages enter the conversation before the buying moment and carry context forward until the user is ready to act.
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AI Structure
Why I Believe Page Weight Is a Structural Advantage
Token cost is metered. When a lighter page communicates the same thing more clearly, that may create a structural advantage for AI systems.
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AI Discoverability
AI Citation Research: Key Findings from WhatsMyArtWorth.com
A live experiment showing how citation, completion gaps, schema, and token cost affect recommendation behavior.
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AI Discoverability
What Is LLM Discoverability?
Discoverability is the recommendation layer: the moment a model sends a user to a website when they are ready to act.
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AI Structure
Feeds vs. Structure: How LLMs Actually Read Your Website
Your site has a human-facing layer and a machine-facing layer; structure is what makes the second one legible to models.
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AI Visibility
How to Control Chat Bias
Chat bias combines personalization and conversational momentum. Learn how to pressure-test outputs and control both.
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AI Discoverability
How to Optimize for AI Search: The Shift from Keywords to Outcomes
Outcome alignment is what makes a website the right answer in a recommendation moment.
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AI Visibility
What Is LLM Visibility?
Visibility is the foundation: whether a model can find, read, and trust what it knows about a website.
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AI Visibility
The Fundamental Misunderstanding of Context in an AI World
Context determines whether a website fits the user in front of the model. Content alone does not.