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> If you make the specs detailed enough so that there's no misunderstanding possible: you've just written code, what we already do today This was my opinion fo

> If you make the specs detailed enough so that there's no misunderstanding possible: you've just written code, what we already do today This was my opinion for a very long time. Having build a few applications from scratch using AI, though, nowadays I think: Sometimes not everything needs to be spelled out. Like in math papers some details can be left to the ~~reader~~LLM and it'll be fine. I mean, in many cases it doesn't really matter what exactly the code looks like, as long as it ends up doing the right thing. For a given Turing machine, the equivalence class of equivalent implementations is infinite. If a short spec written in English leads the LLM to identify the correct equivalence class, that's all we need and, in fact, a very impressive compression result.

AstroBen 8mo ago
Sometimes, yeah. I don't think we're disagreeing What I'd also add: Because of the unspecified behaviour, you're always going to need someone technical that understands the output to verify it. Tests aren't enough I'm not even sure if this is a net productivity benefit. I think it is? Some cases it's a clear win.. but definitely not always. You're reducing time coding and now putting extra into spec writing + review + verification
- bwfan123 8mo ago
  > Sometimes, yeah. I don't think we're disagreeing I would disagree. Formalism and precision have a critical role to play which is often underestimated. More so with the advent of llms. Fuzziness of natural languages is both a strength and weakness. We have adopted precise but unnatural languages (math/C/C++) for describing machine models of the physical world or of the computing world. Such precision was a real human breakthrough which is often overlooked in these debates.