Everyone needs to quit trying to one-shot, and quit assuming AI can’t do it because it can’t one-shot it.
Since the author can enumerate the problems and describe them, it’d be interesting to just use the one-shot pickleball racket model as a starting point. Generate it, look at the problems, then ask an agent to build “fixers” for each problem - small scripts (that they don’t need to build themselves!) which address each problem in turn. Then send the first pass AI output through a pipeline of fix scripts to get something far better but not quite there - and do final human tuneups on the result.
That’s not really how 3D modelling works. You can’t just improve some of the model. You have to improve all of it. Fixing to top of the paddle also changes how the junction at the handle goes and so on. That’s why no one has solved ai 3D modelling yet. It’s like asking a gymnast to learn how to do the second half of a handspring first, and then for step 2 they can learn the first half. It doesn’t work like that.
But if you already know how to 3D model manually, like the author does, why would you spend all that time trying to fix the AI output? For users capable of creating such outputs themselves, the time saving is the point.
If you don’t know how to do it manually then of course that time is well worth it.
It’s about getting to 90% more quickly and getting the job done at 80-90% quality in less time. Potentially an order of magnitude less. If you can do that you can do it again and end up making way more stuff and hopefully more money.
There’ll always be people you can buy handcrafted goods from, who swaeat over every detail. In fact that is my preference when I can afford it - but often I just need a job done so I’ll buy whatever is cheapest and gets the job done.
With AI what’s emerging is a category of “good enough, but way cheaper” products thanks to this mix of AI generated, then human-polished work.
It’s the same idea as using a video editing tool to splice together a bunch of AI videos into an ad, having never gone on site. And it’s quite often exactly what’s needed.
Since the author can enumerate the problems and describe them, it’d be interesting to just use the one-shot pickleball racket model as a starting point. Generate it, look at the problems, then ask an agent to build “fixers” for each problem - small scripts (that they don’t need to build themselves!) which address each problem in turn. Then send the first pass AI output through a pipeline of fix scripts to get something far better but not quite there - and do final human tuneups on the result.