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 →

Mike Austin 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 3 · C 4 · P 3 · Cm 3 3.30

Q Yep. Okay. So a 100,000 dollars. And now did you guys, uh, bootstrap? Are you bootstrapped today or have you raised capital?

A So the mature, so in the early days, we, um, the founders put in, um, sort of founder finance, um, which we did partly from the side of the previous business. So, you know, we were in a fortunate position in that sense, and that's allowed us to do things that typical bootstrapped startup, like our previous one, um, actually, which was fully bootstrapped, um, you know, you just can't do. So, so this time we were able to do things faster. We were able to engineer things better as well from day one, which was quite a luxury, you know, because, um, a lot of startups, you know, have to build things in the quickest, cheapest, simplest way. In order to get it, get it right. Whereas we were able to say, okay, so this is going to be a thousand times bigger in a couple of years time. What do we need to do in order to get that right? So we're able to make some, some good decisions at the start. Um, you know, and that was really very helpful.

AI assessment note: “in the early days, we, um, the founders put in, um, sort of founder finance”

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