You can't unit test for taste

Follow this line of thinking, and the AI-friendly answer is easy: we just have to externalize everything we know, so Claude can implement what I want.

Except that I can't fully externalize myself. Debugging a system takes more resources than running the system. If I could write down everything I know and hand it to a machine, I'd do that, but it impossible.

People aren't books or hashmaps. If you want to build something, you need to use the tools, not teach the tools to use you.

[edit: I'm trying to figure out if there's something to be done about this. Email me if you want to chat -- tr at tern dot sh]

Human: well-scoped argument that does just enough to get the job done with minimal risk.

AI: Extremely clever and correct legal argument that almost any lawyer would have said not to file (at least as written). It tries to burn the world and seriously risks pissing off the judge.

https://www.youtube.com/watch?v=YRXJnKP6Tu0

There is a reason conference talks are always about plain algorithms and data structures.

> QRank is a ranking signal for Wikidata entities. It gets computed by aggregating page view statistics for Wikipedia, Wikitravel, Wikibooks, Wikispecies and other Wikimedia projects

from https://github.com/brawer/wikidata-qrank/blob/main/doc/desig...

This has been my experience, as well, but it’s a really big support. It just needs adult supervision. I can’t understand how vibe-coded apps, actually work.

As far as “taste,” goes, I test my stuff constantly, checking for even minor “friction points,” sometimes, refactoring back to design, in order to resolve issues that many folks would ship. I’m pretty anal, and want my work to be the best experience possible.

I can’t see any LLM coming close to being able to evaluate the user experience, like I can.

I wrote about this a few months back. Rick Rubin is famous for this. I do think it is something that can be trained though, it just needs a lot more context. Taste builds over time through lots of unit tests, through lots of content writing, through an accumulation of product decisions. It’s hard to put it in the individual spec, but it can be teased out of 100 project specs. And when you get to that scale the AI starts to do it pretty well.