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 →

Matt Putra 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
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Answered raw tape D 5 · C 4 · P 4 · Cm 4 4.30

Q If you want to put your brand in front of this highly dedicated audience that's difficult to reach, I'm currently looking for a few strategic partners for the channel. To learn more about sponsorship opportunities, click the link in the description. Let's grow together. How has have your operations changed as you've been more automated? Do you find it getting better, or do you find there slippages in, in things?

A Uh, no, I would say it's better. So I wouldn't say we've saved a ton of time, or maybe we have, but we've redeployed it anyway. We're not just like working less, but I would say our outputs are better. Our understanding is better because again, like these AIs are keeping notes and helping us think better and maybe catching things that we've missed. So I would say our outputs are better. Our, when we working with a client on a thorny issue, obviously all my, my staff have access to Gemini, which just got really smart. And so we're using it. Um, so how do we understand the client's problems better? How do we analyze their stuff better? Um. You know, we're doing like, for example, I'm trying to understand, can you. Predict future sales or CPMs and click through rates with AI given historical data. So we're working on a ton of stuff to help people predict better and make better decisions.

AI assessment note: “Uh, no, I would say it's better. So I wouldn't say we've saved”

Answered raw tape D 5 · C 4 · P 4 · Cm 3 4.15

Q Are you building agents to handle the supply chain and inventory management?

A Not yet right now we are just. Rolling up our sleeves, so to speak, and digging in, obviously we have analysts, so we have analysts, we have supply chain analysts, we have accountants, we've got all that stuff and we're just digging in with elbow grease. I would say when people use automation too early, it tends to backfire. And so what we do in a lot of cases is we pull back on the software. We pull back on the automation and we ask people to have more human conversations. And when, when we fight, when you do that, the whole company starts to run better. And then we haven't gotten to the point yet where they'd be weird. Now we're going back on the software side. Um, Yeah. I'm just finding that that profitability is not a, it's not a math problem. It's a human problem. And so that's how we're working on it.

AI assessment note: “Not yet right now we are just. Rolling up our sleeves”

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