The Exchanges

Every argument clarity score on this site is built from rows on this page. Each question and answer was assessed with names hidden, the host's own answers included, on four things from 1 to 5: directness (does it answer the question asked), coherence (do the ideas follow), precision (concrete details and clear references), compression (says a lot per word). The weighted mix (30/30/25/15) is the exchange score. A person's published score averages their exchange scores on raw tape only, at least 8 of them, shrunk toward the cohort mean. Full method →

Josh Wolfe no published score: only 1 usable exchange on raw tape, and a fair score needs 8+ record → ← everyone

Every exchange below was scored with names hidden, four dimensions each from 1 to 5. An exchange's score is 0.30·directness + 0.30·coherence + 0.25·precision + 0.15·compression. The published score averages the raw tape exchange scores and shrinks small samples toward the cohort mean, so five great answers can't beat twenty good ones. Produced feed rows count only toward coarse estimates, never toward a full score.

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Answered raw tape D 4 · C 4 · P 4 · Cm 3 3.85

Q Open router. Routing. Everyone wants cheaper stuff. AI, the mixed multiplication commodity. There's no reason to pay a PhD to fold your laundry, but you also don't want to give open router all your data, or do you, or do you not care? Like, how does that play out?

A I, I do think that the bigger question here, which is going to also bifurcate, it's not going to be one takes all, is open versus closed. And, um, I am saying this obviously with a bias, as I've said in the past, that where you stand on the issue depends on where you sit in the cap table and where large investors and hugging face, which made a lot of news over the past few weeks. But I think that the future is for the more sophisticated users who serve for the enterprise, it's going to be your longitudinal proprietary repository silo of data that is yours. That is exactly as we were just talking about, uh, not ingested by the machines. And if you have that and can run open source models, On that time series of data that is exclusively yours, whether you're a pharma company, a finance company, insurance company, a retail company, a venture firm, increasingly you are realizing that to get the benefit, you're giving a benefit. And you're going to say, I'm not going to give that data, especially if I'm not going to give that data and watch as one of the closed labs competes me away. And you saw that first with Figma, which was sort of scary. And I think the push now from Anthropic and opening eye to go into pharma and pharma companies saying, well, do we want to do this? Do we want to give them our data and then potentially open up competitors? And I think there's a big move right …

AI assessment note: “you are going to say, I'm not going to give that data”

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