Resources
AI describes your brand. You author the source.
Essays on the data, the stack, and the work brands have to do to show up correctly in ChatGPT, Gemini, Claude, and Perplexity.
Manifesto
May 2026
What the Model Does Not Know
The case for brand authorship in the AI commerce era. Human-in-the-loop is not a workflow constraint — it is the architectural commitment that lets a brand keep speaking for itself when models are answering for everyone else.
Read essayComparison
May 2026
The 2026 AI Commerce Stack
Feed managers, AI visibility trackers, and canonical source layers are pitching brands the same problem. They sound similar. They are not. A buying frame for the leads being asked to choose.
Read essayUse case
May 2026
How AI Gets Your Brand Wrong
When ChatGPT or Gemini describes your products incorrectly, the instinct is to blame the model. The model isn't the problem. The problem is that your product truth lives in five internal systems and almost none of it has been published to the layer the model can read.
Read essayThesis
May 2026
Why Brands Need Trevise
When customers ask AI agents what to buy, brands are being described by data they don't control. Trevise is the canonical layer that lets brands sell to AI agents the way they sell everywhere else — like themselves.
Read essay