I disagree that anyone should need LLMs for Blender, for example, because Blender is designed by people to be understood and used by people, even if it requires a learning curve. It sounds a bit dangerous to build new things we don't understand, or worse, reduce our understanding of what we currently use because (only after studying our use of the same technology) an LLM apears able to replicate it, mostly.

I'm reminded of Sam Altman's performative helplessness on Jimmy Kimmel, when he described being unable believe a baby without ChatGPT. That's something I believe humanity has been capable of doing for a good portion of its existence, and not something we should give up to the hands of a yet-unproven, yet-unprofitable technology.

It also sounds like people with little ability can use this argument as a way to say “look how difficult this is for humans”

While it’s just a “you” problem. Some folks have better skills, knowledge and comfort with difficult subjects. And that’s fine.

Surely there's a middle ground where improved APIs can be leveraged by both people and LLMs alike while keeping those APIs approachable? Why is it necessary that changing the python APIs would lead to "need[ing] LLMs for Blender"? I'm nowhere close to an AI maximalist but this criticism seems grounded in execution concerns. I'm definitely not saying that they won't mess this up and make the APIs overly complex, I just don't think that's necessarily going to be the case.

I propose that, for some software, the learning curve is becoming harder to surmount.

Further, I'm suggesting "designed by people to be understood and used by people" might be a hurdle for some future software we might envision.

(Altman's performance is orthogonal as I'm suggesting a new level of software that has not yet been written/conceived.)

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