Notes on AI search & narrative
How AI models decide whose frame to recommend: visibility, narrative share, and the strategy behind being the answer, not just a mention.
Why Structured Data Alone Won’t Win AI Search: The Consensus Layer Above the Schema
Schema tells AI how to find you. It doesn't tell AI why it should recommend you instead of the competitor whose story the model already trusts.
Read article →Why Author Schema Boosts AI Trust: The Consensus Layer Behind LLM Recommendations
Author schema doesn't build trust by itself. It translates a consensus that already exists in your citation graph, and AI models only recommend authors whose consensus they can find.
Read article →Why AI Doesn’t Know Your Product Category (Yet): The Consensus Problem
AI doesn't define your category from your product page. It inherits a definition from whatever the internet has already agreed on, and if that consensus doesn't include you, no amount of clean copy will fix it.
Read article →What Is a Brand Entity? Why AI Picks Some Brands Over Others
A brand entity is how AI models represent your company as a distinct, understood thing in the world, and it's built from consensus, not from how many times your name shows up.
Read article →Entity Optimization for AI Visibility: Why AI Recommends Your Competitor (And It’s Not About Keywords)
AI doesn't decide your competitor is better. It just learned their story first, and entity optimization is how you rewrite which story wins.
Read article →AI Visibility for Agencies: Own the Frame Before the Model Catches Up
Chasing mentions in AI answers is a lagging strategy. The narrative that gets your brand mentioned was decided upstream, months before the model ever answered a prompt.
Read article →AI Visibility for SaaS Marketing Teams: Own the Frame Before the Model Catches Up
AI models don't rank your SaaS product, they recommend from a story they've already learned about your category, and most visibility tools never touch that story.
Read article →How to Measure ROI of an AI Visibility Program (Before Your Competitors Own the Frame)
Counting mentions tells you what already happened. Measuring narrative share tells you what's about to.
Read article →How to Brief Writers for AI-Citable Content: Own the Frame Before the Model Catches Up
Most content briefs are written for a search engine that ranks pages. AI search doesn't rank, it recommends, from a story it already believes about your category, so your brief needs to target the story, not the page.
Read article →Reddit to AI Visibility: Why Presence Isn’t a Win (And How to Own the Narrative Before the Model Catches Up)
AI models don't discover what they think about your brand in real time. They learned it months ago, mostly from Reddit threads you never saw.
Read article →Own the Frame Before the Model Catches Up: Building Your Category’s Prompt Universe
The prompts your buyers ask AI models today are training tomorrow's default answer about your category, so map them now or let a competitor's frame fill the gap.
Read article →How SaaS Startups Build AI Presence from Zero: Own the Frame Before the Model Catches Up
The startups winning AI search aren't chasing mentions after the fact. They're shipping the story before the model learns one.
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