It's kind of funny-- I'm a technical visual artist, classically trained (former) chef, and spent a long time as a web developer in an environment where people breathlessly spoke about the possibility of LLMs. (Auto-correcting OCR was my pet wish that I never fulfilled.) It's been... interesting seeing layman's usually naive and mistaken takes on generative AI performing these functions.
The difficult part of recipe development is testing, and professional recipe authors pay a lot for it. (It was regularly available pickup work when I was in culinary school.) Professionals don't use recipes like home cooks do: ours are much simpler, tend to combine ratios and amounts with known techniques, and assume knowledge that most home cooks don't have. Home cook recipes tolerate people who don't really know what "4 lbs turned radishes glace w/sherry" means, where nearly any professional cook familiar with classical european cooking could grab the half dozen ingredients and equipment without clarification and perform the technique almost identically to another cook across the world. It's not rocket science, but even with clear instructions, there's a lot of technique there that you just have to do at least a few times to get a sense of it in a really basic way.
Writing recipes for home cooks poses the same challenges developers have writing documentation for people who aren't familiar with the codebase they're documenting. Home cooks consistently execute things like "Saute" much differently than a chef might assume they would, use seasoning very differently, measure doneness by the amount of time cooked rather than using internal temperatures, textures and smells, need measurements for "pinches" of things and use volumetric measurements instead of weights, and and all sorts of other things. For a home cook recipe, the professional instruction, "hard sear, glaze, and brown in the broiler" would need likely need specific times, settings, pans, and things like that... and the temperature of home cooking equipment, the initial temperature of the ingredients, slight variations in salt or sugar content, all have a significant chance of making that recipe fail. I guarantee you that when, say, Gordon Ramsay writes a cookbook, rather than writing the recipes himself, he goes into a R&D kitchen, cooks the dishes with those cooks who know how home cooks do things, and they write the actual recipes that go in the books.
So like almost every other "hey lets replace some creative/technical person with this generative AI" initiative I've seen, this would do the easiest 95% that takes 5% of the time while not addressing the most difficult 5% that takes 95% of the time. When someone asks Midjourney to make, oh, say, a sexy elf in the style of Thomas Kinkaid or whatever Midjourney users want these days, they might not be a professional artist, but since they're the consumer, they can judge whether the elf looks appropriately sexy or stylistically enough like Thomas Kinkaid. Getting a recipe spit out like this requires technical judgement that any user who'd rely on such a device would almost certainly lack.
Fortunately/Unfortunately it seems pretty difficult to devalue professional cooking as a skill any more than it already has been, and your average pro doesn't have much exposure to this sort of market anyway, so I'm not really worried about industry impact compared to, say, concept artists for video games... Though I think workaday utility developers are more squarely on the chopping block than most. However, I feel for the home cooks who'll faithfully follow these recipes expecting similar results to what they get from foodnetwork.com, simply recipes, the new york times food section, or whatever other source they get recipes from.