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 →

Sherry Jiang no published score: only 2 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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2exchanges match
2on raw tape
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Answered raw tape D 5 · C 5 · P 4 · Cm 4 4.60

Q Yeah, this is cool. Um, this is this, what's cool about this and the lens I'm using for, for everyone is This could be applied to a million niches. There is, and I'm curious, like, have you thought of other niches where this could work? Like peak for X.

A Yeah, I mean, I think that, uh, like nutrition is definitely like eating, uh, eating, diet, health, kind of all, all sort of related, right? Um, now I'll tell you like a habit I wish I had that I do not have because it takes too much effort. Um, I want to be more specific about, like, The types of food that I am eating to, like, reach my goals, right? Whether it's like, oh, I want to, like, build muscle for this, like, competition I'm doing in the summer. Maybe for others, it's like, oh, I want to cut, right? Um, Now, getting, like, uh, everything tracked, and then being able to, like, personalize the goal, then being able to, like, plan the meal, and then figure out where to buy the meal, because, you know, you have to go out and get groceries, cook, whatever, and then, like, give continuous feedback around how the plan is going, right? Because iteration, like, it might not be perfect the first time. Like, I would love that, right? I mean, if someone's building that today, like, I, I, Would love to take a look, but it's the same kind of concept of, like, you know, you, you have to, like, capture not just the tracking and the numbers part. It's like there's so much more, so many more steps to ultimately getting to you taking an action and then seeing the results of the action. So I think this applies to so many different, so many different areas where, um, you know, where there…

AI assessment note: “nutrition is definitely like eating, uh, eating, diet, health, kind of all”

Answered raw tape D 5 · C 4 · P 3 · Cm 3 3.90

Q Yeah, so the rule of six, you get feedback, you start getting insights. These insights, by the way, relevant for anyone building an AI app. What's next?

A Yeah, you start to build. Um, so, uh, we basically took this, um, and spent about One and a half months actually building it out before we launched in the app store. And, um, for anyone who's launching a mobile app, uh, you sometimes get asked, like, should you do test light? Should you do, like, the pre-orders? Like, do you do a waitlist? Um, we just, like, sent it, and we're like, you know what? Like, let's just get it out there, right? And, um, you're never gonna feel ready, and it's fine. There's gonna be bugs, but that's okay. That, you don't get real feedback until you have Real users. So this is what the app looks like today. So obviously a lot more, uh, you know, design elements in here that are way more colorful than it was created, but you'll start to see like there's actually parallels, right? This, this page essentially was this, right? But we like added more, um, you know, cards that felt like a lot more readable. We added these like stories basically, which are like, you know, Nearly daily check-ins. Now, uh, this is a mock-up, so I realized, uh, you know, there's some dates that look kind of funny, but, uh, basically these are, like, almost like Instagram stories, right? Um, so we, uh, so on this screen, um, we did something where we wanted to, like, take what was familiar with two people and other apps, so, like, these, like, little circular icons are familiar i…

AI assessment note: “Yeah, you start to build. Um, so, uh, we basically took this”

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