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 →

Emil Eifrem 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 4 · C 4 · P 4 · Cm 4 4.00

Q I presumably startups are easier to onboard because they have less context than the, the, the larger companies. So I guess what have you prescribed so far in terms of like, you know, whichever segment you want? Uh, honestly, both are interesting to me. What are the best practices so far? Like, you know, how, how do they even get started?

A It depends on which altitude you operate at, right? Like if it's a, if it's a single startup, it's not just, there's one product, but the product is the company. So that's then everything, right? And that's very different if you look inside of the enterprise context, right? Because then we engage in, in two levels, right? One is the scope of a single application, a single project, right? And the other one is more enterprise-wide. This, let me talk about the, the, the last one for a moment, because this is a big change that has happened since, certainly since the two years ago, the, the, the graph rag talk. A clear pattern that we're seeing happening is We tend to call it a knowledge layer, but we bump into a lot of enterprises, and the problem is, ok, Every single data source is going to have some kind of an MCP endpoint here, right? Okay. I want to give my agents access to that. So like, what can I do? Either I give my agents access to all of the MCP endpoints and let it figure it out, right? The problem that they run into is that yes, that works, but like some of the data is going to be conflicting, right? And so we just talked about, we have a cloud service, right? Even for me, like when I tried to figure out like how many customers do I have on my cloud service? Like I go to the actual cloud platform and I ask, and we have, let's call it. 3000 customers, right? That means h…

AI assessment note: “A clear pattern that we're seeing happening is We tend to call it a knowledge layer”

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