Probabilistic generation will be weighted towards the means in the training data. Do I want my code looking like most code most of the time in a world full of Node.js and PHP? Am I better served by rapid delivery from a non-learning algorithm that requires eternal vigilance and critical re-evaluation or with slower delivery with a single review filtered through an meatspace actor who will build out trustable modules in a linear fashion with known failure modes already addressed by process (ie TDD, specs, integration & acceptance tests)?
I’m using LLMs a lot, but can’t shake the feeling that the TCO and total time shakes out worse than it feels as you go.
>Am I better served
For anything serious, I write the code "semi-interactively", i.e. I just prompt and verify small chunks of the program in rapid succession. That way I keep my mental model synced the whole time, I never have any catching up to do, and honestly it just feels good to stay in the driver's seat.
I don't even see how an LLM (or frankly any recipe) that is a summary / condensation of various recipes can ever be good, because cooking isn't something where you can semantically condense or even mathematically combine various recipes together to get one good one. It just doesn't work like that, there is just one secret recipe that produces the best dish, and the way to find this secret recipe is by experimenting in the real world, not by trying to find some weighting of a bunch of different steps from a bunch of different recipes.
Plus, LLMs don't know how to judge quality of recipes at all (and indeed hallucinate total nonsense if they don't have search enabled).
It's funny, I actually know quite a few (totally non tech) people who uses (and like using) LLMs for recipes/recipes ideas.
They probably have enough experience to push back when there's a bad idea, or figure out missing steps/follow up.
Thinking about it, it sounds a bit like LLM usage for coding where an experienced programmer can get more value out of it.
Whether or not you think you can get "good" recipes out of it will also depend on your experience with cuisine and cooking, and your own pickiness. I am sure amateurs or people who cook only occasionally can get use out of it, but it is not useful for me.
Cooking is a very different world from coding: recipes aren't composable like code (within-recipe ratios need to be maintained, i.e. recipes written in bakers ratios/proportions, steps are almost always sequentially dependent, and ingredients need to complement each other) and most sources besides the few good empirical ones actually verify anything they make, which is a problem, because the training data for cooking is far more poisoned.
