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 →

Brendan Falk no published score: only 1 usable exchange 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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1exchanges match
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Answered raw tape D 5 · C 5 · P 4 · Cm 4 4.60

Q Yeah, no, and I think, like, uh, what, you know, if I'm in your shoes, I'm like, man, these people don't even know what Anthropic is. Why would I go be the palantir for enterprises, you know?

A I honestly got off the call sometimes with these customers and just went, man, you can give me two engineers in, like, a week or two, and we could probably save you a million dollars, but it was just the, and it wasn't this company's fault, they're just not technical companies. You know, I bucketed these companies into tech companies and non-tech companies, and within non-tech, it's Are they technical or non-technical? You know, do they have good in-house engineering resources? So take like Goldman Sachs. They're actually quite technical. They've got tens of thousands of engineers, whereas a lot of other non-tech companies are really not technical and they're outsourcing to Accenture. And so one of the key things that I saw was these companies knew that AI was adding value. They saw on the news, hey, Klarna has saved tens of millions of dollars by, uh, you know, customer service automations, and Amazon saves this amount, and this company saves hundreds of millions of dollars here. So they, they saw that AI was creating real value. They were playing around with themselves saying it was creating value and they just, they had no idea how to actually get it done. And so what I ended up seeing is they were all going to Accenture. And what was happening is the board was yelling at the CEO saying, where's our AI strategy. The CEO was yelling at the SVPs and other C-suites saying, what…

AI assessment note: “I honestly got off the call sometimes with these customers and just went, man”

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