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 →

Anshul Ramachandran 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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Q Can you spell out what you couldn't do in VS code? Because I think when we did the, the cursor episode explain, then everybody on agronews is like, oh, why, why did you fork? Why you could have done it in an extension? Like, can you maybe just explain more of those limitations?

A I mean, I think a lot of the limitations around, like, APIs are pretty well documented. I don't know if we need to go, necessarily go down that rabbit hole. I think it was when we started thinking, okay, what are the pieces that we actually need to give the AI to get to that kind of, you know, emergent behavior that Bruin talked about, right? And, and yes, we were talking about all the knowledge retrieval systems that we've been building for the enterprise all this time. Like, that's obviously a component of that. You know, we were talking about all the different tools that we could give it access to so they can go, like, do that kind of terminal execution and things like that. Then the third main category that we realized would be like kind of that magical thing where you're not out there writing out a PRD, you're not scoping the problem for the AI, is that if we're actually being able to understand the kind of the trajectory of what developers are doing within the editor, right, if we actually be able to see like, oh, the developer just went and opened up this part of the directory and tried to view it, then they made these kind of edits, and they tried to do like some kind of commands in the terminal, and if we actually understand that trajectory, then our ability for the AI to just be immediately be like, Oh, I understand your intent. This is what you want to do without you…

AI assessment note: “limitations around, like, APIs are pretty well documented. I don't know if we need”

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