How AI Assistants Select Brands to Cite

Report TR-2026-001 breaks the route from a user's question to a shortlist of named brands into four steps: retrieval, candidate assembly, verification, and rendering. Each step removes brands for its own reason, and being findable in ordinary search only clears the first one. The episode also covers two recurring failure patterns and why one test prompt tells you nothing.

• Retrieval — long questions get split into narrow ones, so pages built around a single narrow topic get fetched
• Candidate assembly — a name in a list or a logo with no text around it leaves nothing to extract
• Verification — a spec only the vendor states counts for less than one repeated by outside sources
• Rendering — limited answer length favours brands whose category takes a few words to state
• Two failure patterns: brands widely mentioned but never described, and brands only they describe
• Volatility — repeat answers vary, so position needs repeated observation across phrasings

Full report: TR-2026-001: How AI Assistants Select Brands to Cite

Trellner Research — trellner.com

What is The Trellner Review?

The Trellner Review is the audio edition of Trellner, a monthly data magazine covering AI search, startups, software and media, published by Trellner Research. Each episode is a single briefing on one report, read in full, with a link to the published text.