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757 points alihm | 1 comments | | HN request time: 0.25s | source
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meander_water ◴[] No.44469163[source]
> the "taste-skill discrepancy." Your taste (your ability to recognize quality) develops faster than your skill (your ability to produce it). This creates what Ira Glass famously called "the gap," but I think of it as the thing that separates creators from consumers.

This resonated quite strongly with me. It puts into words something that I've been feeling when working with AI. If you're new to something and using AI for it, it automatically boosts the floor of your taste, but not your skill. And you end up never slowing down to make mistakes and learn, because you can just do it without friction.

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1. benreesman ◴[] No.44470531[source]
I don't know much about Ira Glass and I'm not going to be a 5 minute wikipedia expert about it, so maybe I'm missing out on very relevant philosophy (I hope someone links the must read thing), but those would be very intentionally inverted meanings of the taste/skill dichotomy.

LLMs are good at things with a lot of quantity in the training set, you can signal boost stuff, but its not perfect (and its non-obvious that you want rare/special/advanced stuff to be the sweet spot as a vendor, that's a small part of your TAM by construction).

This has all kinds of interesting tells, for example Claude is better at Bazel than Gemini is, which is kind of extreme given Google has infinite perfect Bazel and Anthropic has open source (really bad) Bazel, so you know Gemini hasn't gotten the google4 pipeline decontamination thing dialed in.

All else equal you expect a homogenizing effect where over time everything is like NextJS, Golang, and Docker.

There are outlier events, like how Claude got trained on nixpkgs in a serious way recently, but idk, maybe they want to get into defense or something.

Skill is very rarely the problem for computers, if you're considering it as district from taste (sometimes you call them both together just skill).