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 →

David Rogier no published score: no usable exchanges 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.

clear all ✕
1exchanges match
0on raw tape
0redirected or not addressed
Partly produced feed D 2 · C 4 · P 4 · Cm 3 3.25

Q Okay, very cool. So walk me through, walk me through kind of like why you did this, because this space is crowded, right? And we've got like Udemy, like Udemy, Udemy, I don't know how you say the name, whatever. Udemy, CreativeLive, I'm sure there's others, LinkedIn Bot, the platform, they're kind of getting into this now. Why do this? Yeah, Linda, yeah.

A Um, Okay, it started, um, so I actually was working for a VC fund here in, here in the Bay Area, as in, I was in, I was a tech investor, um, and I miss building stuff, and I actually went to the head, I went to the, I went to the head of the fund I was working at, and I was like, hey, thanks so much, but I wanted to start to build something. Um, I worked, uh, for his, the guy who ran the fund, his name is Michael Deering at Harry Um, Michael Deering is probably like one of the best seed Investors in the Valley. Uh, he's, he might be a, he might be a genius. Um, he is way smarter than I am. Um, and, um, so I, I went to Michael. I was like, Hey, thanks so much. I want to go start selling. I am not, I do not know what. Um, and Michael wrote me a check for about half a million bucks and told me to go think of an idea, um, which was really nice of him. And I did not want to mess that up. Um, so I thought long and hard about what is it I want to do. I did lots of tests. I did polls. I built fake websites. And what I came back to was what I learned from my, uh, grandmother. Um, my grand, my, my grandmother helped raise me. She, she, she, she was raised in, in Poland. Um, while she was on a, On a vacation at the age of, like, 18, um, the, the, the Nazis invade Poland. Um, they, they, they, they, they take everything she had. They also kill her, they also kill her, her, her, they kill h…

AI assessment note: “I thought long and hard about what is it I want to do.”

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