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 →

Dave Hurwit no published score: no usable exchanges on raw tape, and a fair score needs 8+ · coarse estimate ≈4.0/5 from 4 produced feed exchanges 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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4exchanges match
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Answered produced feed D 5 · C 5 · P 4 · Cm 4 4.60

Q Okay. What was the pain point? Like you were sick of paying 200 dollar application fees. I mean, it helped us understand the pain.

A Yeah. No. So, you know, she was a kid with, within the system that has relative privilege, right? She had two parents who'd gone to college. Um, she had a decent high school guidance counselor at her public high school. We hired her a private guidance counselor to help her through the process. Um, and we put together a list. Um, we drove her out to the middle of nowhere in New York state to visit the first school. And we drove onto campus and she said, no, no, no, no, no. I'm not even getting out of the car, dad. This is the wrong place. I said, well, no, you're, you're getting out of the car. Um, but let's, let's go tour and then let's talk about it. Right? So we went and had the tour. Got back in the car. I said, all right, tell you what you jump on Spotify and improve the mood here with a better song. Um, and I'm going to jump on Yelp and we're going to find a great place to have dinner tonight. And we're going to talk this through and Spotify and Yelp nailed it. Right. Um, and it occurred to me that their matching algorithm is so much more sophisticated than how we were trying to make this quarter million dollar decision about where to go to college. So if you, if you sort of go from there and say, um, The biggest part of every school are the graduates of that school. They are the people that have achieved the success that every incoming freshman is looking for. And if you …

AI assessment note: “matching algorithm is so much more sophisticated than how we were trying to make this”

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

Q And how do you make money for the school pays you or the daughter pays?

A Uh, no, right now the model is the school pays. Schools are collectively spending about fifteen billion dollars a year on advertising, marketing, and admissions, uh, costs, and this is a system that is profoundly unequal, right? There, there is significant advantage to the kids that have money, um, who have family history of education, and so I really, there's a very much of a mission orientation for us to say, how can we use technology to level the playing field? Not only for the students, uh, that don't have the means coming into the system, Um, but also for the schools that are sort of in that middle and lower tier of, uh, of access and, and of, and of financial stability.

AI assessment note: “right now the model is the school pays.”

Partly produced feed D 3 · C 4 · P 4 · Cm 3 3.55

Q Okay, so low-cost base. How did you find the agency to trust with the early code?

A Um, one of our investors, um, so, you know, Burlington, Vermont's a fairly small, tight community. The, the, the most successful SaaS company out of Burlington is a company called dealer.com. Um, and so I went in search of dealer.com folks. Um, and within Burlington, you're only a few degree degrees of separation from any one of those guys. Um, so I was able to, uh, meet, um, and build a relationship virtually. With, uh, one of the, the co-founders of dealer.com, which went on to exit for about a billion dollars initially. Um, he was their CTO who turned into their CEO. Um, and he's led the product development side of the business, not technically as a founder, but he has put money into the business, um,

AI assessment note: “one of our investors, um, so, you know, Burlington, Vermont's a fairly small”

Redirected produced feed D 2 · C 4 · P 4 · Cm 3 3.25

Q Oh, that's great. Okay. So, so, I mean, can we define active as you've placed at least one enrolled student at those schools?

A Well, for most of them, they've, they've signed up in the last few months. Sort of kick off, generally speaking, after Labor Day. So we're getting those guys in place, um, and the, the thing they get from us is the ability to use our matching quiz, right? So we, we help, we administer their, our quiz with their recent graduates that helps to build their specific school code. They then use the quiz in their marketing. So they're out there sending email messages to prospective students saying, find out, you know, how much of a hokey are you? How much do you have in common with, um, the Tar Heels? Um, and, and you can take this quick quiz and it'll return to you some data about your social fit and your learning culture fit, um, with each specific school.

AI assessment note: “for most of them, they've, they've signed up in the last few months.”

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