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 →

M.C. Srivas 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
0redirected or not addressed
Answered raw tape D 5 · C 4 · P 4 · Cm 3 4.15

Q And still on the, uh, entrepreneurial journey part, so, so what were the, how do you, how do you start? How do you hire employees?

A Yeah, so it's a, it's a big, big challenge, right? I mean, uh, you have to hire friends first, because, you know, think about this. I, I had a bunch of friends, and I was trying to hire, and this actually happened to me. I had twenty million dollars in my pocket, but no building, right? And I tried, I'm trying to hire people, and they come and say, and they look at this little room with no chairs, And, you know, we had a, taken, you know, unscrewed a desk, ah, sorry, a door, and used it as a desk, because we didn't have a desk. And, of course, some guys who came in were very excited that, I'm getting into a company really early. And the other guy said, you don't have a coffee machine, I'm not working here. They would just walk out. So it was a challenge, uh, trying to hire in the beginning. I think that's the number one problem, I think. And you have to try to hire people who are not like you. I mean, basically, that's the first advice. Because you tend to be attracted to people who are like you, and in the beginning you really want a big variety of people, and not from the same DNA. It's very important. So, uh, that, that was a big challenge.

AI assessment note: “you have to try to hire people who are not like you”

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