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 →

Sarah Wang 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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1exchanges match
1on raw tape
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Answered raw tape D 4 · C 5 · P 4 · Cm 4 4.30

Q the, the, the reason for this is, is triggering, uh, yeah, we are, like, I'm hiring ops, ops people, um, a lot of founders I know are also hiring ops people, and I'm just, you know, it's opportunity since you're, you're also, like, basically helping out with ops with a lot of companies. What are people doing these days? Because it's still very manual as far as I can tell.

A Hmm, yeah. I think the things that we help with are pretty network-based, um, in that, It's sort of like, hey, how do I shortcut this process? Well, let's connect you the right person. So there's not quite an AI workflow for that. I will say as a growth investor, Claude Cowork is pretty interesting. Like for the first time you can actually get one shot data analysis, right? Which, you know, if you're going to do a customer database, analyze a cohort retention, right? That's just stuff that you had to do by hand before. And our team, the other, it was like midnight and the three of us were playing with Claude Cowork. We gave it a raw file. Boom. Perfectly accurate. We checked the numbers. It was amazing. That was my, like, aha moment. That sounds so boring, but, you know, that's, that's the kind of thing that a growth investor is like, you know, slaving away on late at night, um, done in a few seconds.

AI assessment note: “That's just stuff that you had to do by hand before.”

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