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 →

Jeremy Bell 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.

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Answered produced feed D 5 · C 5 · P 4 · Cm 4 4.60

Q I mean, who cares, right? It's a beta list, but what is important is how you're building it, right? So how are you, how are you building such a big beta list? What's the tactics?

A Yeah. So the way we've been, we've been building out the list has been, it's predominantly, it's been organic. Um, there's been a lot of word of mouth. Some of the people that are in the, we do have a closed beta. Those that are using it are also referring coworkers and stuff that comes through that process. Um, we also have set up a, we'll describe as like a social listening kind of program where we have some things set up, uh, that are looking for people who are tweeting and posting stuff on Reddit and LinkedIn and those, those messages that are talking about things that are related to what we're, we're building. Um, those get brought to us and then we usually respond to them, um, In those respective channels, we found that to be a pretty effective method. It doesn't scale. Like, I don't think this will, you know, work for that much longer. Um, but it's been a perfect kind of slow. What are you using?

AI assessment note: “predominantly, it's been organic. Um, there's been a lot of word of mouth.”

Answered produced feed D 5 · C 5 · P 4 · Cm 4 4.60

Q And, and you, I mean, was that, I mean, I want to get into your personal financial situation, but do you make enough there where you have whatever a 1,000,002 million dollars for a buffer, you can sort of do whatever you want as, as the next swing at the startup bat?

A Um, when I, no. So when I left that one, um, I started my first startup. I mean, that was again, entirely bootstrapped. Like I didn't, I didn't participate in that exit whatsoever. Um, I raised a bit of money and then ended up exiting on that one and sold it to a company called precision nutrition, um, made, you know, basically made all of our existing investors and myself like whole. So it wasn't like a huge liquidity event by any stretch enough that, you know, it was a good learning experience where no one walked away losing any money. Um, Coming out of that though, I, to be frank, I had a bit of crypto that I had, uh, I had put aside and there was a little bit of money that I had that I was able to pay basically myself, um, while I worked through the, the, the, the little bit upfront, um, that kind of kept me going. And then, uh, then we raised the friends and family around to kind of do it properly.

AI assessment note: “no. So when I left that one... I didn't participate in that exit whatsoever.”

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