Field notes from the AI shelf.
Short, practical takes on AI catalog readiness, recommendation eligibility, product data quality, retrieval behavior, evidence, and governance for modern commerce teams. New posts appear below as we publish them. Longer-form research lives on Insights.
Latest field notes
SEO, AEO, GEO: three ways to show up, and the one your catalog decides
SEO, AEO, and GEO are three ways to show up in search. Getting mentioned is not the same as being recommendable, and that is decided by your catalog.
Read →What making our own site AI-ready taught us
We held our own site to the standard we measure for client catalogs: five AI-readiness gaps a mainstream website builder hides, and how we closed them.
Read →What AI assistants get wrong about real catalogs
The average catalog is only about half-ready. An honest look at where AI assistants miss, misread, and misrepresent real product catalogs.
Read →Why good SEO won’t save you in AI shopping
Great SEO gets you found. It was never built to make a product confirmable, trustworthy, and recommendable to an AI assistant.
Read →The 5 questions an AI assistant asks before recommending your product
The five plain-English checks an assistant runs on your catalog before it will put a product on the shortlist.
Read →Your catalog is talking to robots now. Here’s what they hear
Every product page now has two audiences. Here is what the machine actually hears when it reads yours.
Read →From the search bar to the shopping agent: the discovery shift in 5 charts
The move from the search bar to the shopping agent, in five sourced charts every commerce team should see.
Read →Invisible to AI is invisible to revenue
A bad AI recommendation is the loss you never see. Why eligibility, not familiarity, is what converts.
Read →Want to see how AI reads your own catalog?
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