In modern AI search, language models act as re-rankers over results retrieved by traditional rank factors. Even in the absence of traditional ten blue links there's always a clear and measurable ordinal value to each brand mentioned in model's generative output.
Here's how I test this: https://t.co/J0syitvMg7
Google's grounding pipeline, for instance, decomposes a query, retrieves ranked sources, then has the model select sentence-level snippets under a fixed budget. Ranking #1 buys you a larger share of grounding, though being selected is a separate problem [1].
A model's parametric memory carries its own relevance priors, and those priors are an emerging class of factor shaping which results get selected and surfaced. A brand the model already perceives as relevant for a topic is more likely to be grounded when supplied as a source [2], and these priors are measurable: you can rank brands by how deeply they're embedded in a model's associative structure [3].
To be clear about terminology: when I say model rank factors I mean model-side selection factors. They're distinct enough from Google's ranking signals that I've taxonomized them as alignment, substance, architecture, style, framing, and proof, and built a ranker that simulates the model's source-selection step to measure which of them actually move a page's standing [4].
My current focus is understanding this behaviour through systematic observation of inputs and outputs, probing models directly and tracking how associations shift over time [5].
Direct steering and white-box interpretability aren't available for closed-weight models like Gemini, GPT and Claude, so this black-box approach is the practical one. It's the same logic applied psychology, psychiatry and cognitive science already use.
[1] SRO & Grounding Snippets https://t.co/SkUAnwIBaH
[2] Primary Bias on Selection Rate https://t.co/nzSowG1OzF
[3] AI Brand Authority Index https://t.co/oMiu8CHQlF
[4] Content Optimizer https://t.co/J0syitvMg7
[5] Beyond Rank Tracking https://t.co/iMT0A6mcyg
@NameBio@doronvermaat@afternic@eftycom FWIW I think sellers also need the ability to add an incremental % to LTO rates. This is the one thing I feel is still missing. On Afternic - I'm not a fan, but hard to ignore their massive funnel. Hate their LTO implementation FWIW.
@NameBio@doronvermaat@afternic I honestly don't have enough data. I shied away from LTO after getting burnt a few times, and only restarted using since @eftycom added this ability (and also upgraded bulk upload to support it - kudos @doronvermaat). The old saying: "a bird in the hand" still holds true IMO.
@NameBio@afternic Another thought - it's not just financial risk. There can also be very high reputational risk. I've had at least 1 cancelation where the domain was used to scam crypto owners for a month, and it's probably worthless now as a result.
@doronvermaat@NameBio@afternic This was one of the clear positives with Efty's implementation - being able to set down payments at the name level is a huge bonus. Kudos for adding this into bulk upload so quickly!
@NameBio@afternic Excellent analysis and share. I think LTO has been trumpeted as a godsend by the marketplaces, without much consideration to the risks. Another issue is that 0% rates actually devalue your assets - BIN and LTO pricing shouldn't be the same, but most marketplaces enforce it.
@YoungbloodJoe Ask it why. Ask it to elaborate on how it drew this conclusion. Ask it to reason through the process. You never know - it could just be making up what it thinks you want to hear, or it could be basing this on some hidden gem. Worth digging to see IMO.
@gaganghotra_@PeterMindenhall He's far too clever to come out backing this for it to be a run-of-the-mill genAI content campaign. I suspect the doubters may be wrong here. Like I said, time will tell. Lots of eyes on it now.
@gaganghotra_@PeterMindenhall In all fairness, this may be its saving grace. I'm going to hazard there's far more to this than genAI spitting out new content, no human review etc. He's already stated that a lot of this is content refresh. Time will tell.