Pre-AI version: Oops, you laid off the higher-salaried people without having them train their replacements, so bring them back, long enough to do that.

Now, that training[*] will be for both AI models and lower-salaried hires.

Perhaps a second mistake by those who thought they didn't need their most experienced people: Now they think they just need to train the AI better, and then new-grad "AI native" hires will be the most cost-effective way to operate/oversee the AI and do whatever it can't.

[*] edit: originally typed "replacement" when I meant to type "training"

> He's saving face while almost certainly trying to figure out how to make the new systems work so that next time he won't need to rehire engineers.

Yup. They jumped the gun. Now they need to hire them back so they can loot their expertise and never hire another senior. I'm not saying this will work, but it's pretty obviously the plan.

Yes.

And for people focusing too much on AI, Xiaomi kicked their first vehicle into production with a fully automated factory three years ago [0]. That's where the industry is going and has tried to go for decades now.

They might want to also reduced head out on the designing side, but it's also an ongoing trend that started before the AI boom.

That's not an industry that will keep hiring as much as they did in the past, however it turns out.

[0] https://youtu.be/v6jb6PP4APc

Maybe. That's one interpretation. A lot of hiring/firing decisions get read through the lens of AI, hard pro or hard con. Reality is always a mixed bag. They certainly will want to try to build up a better automated pipeline, but the question is can they, and can they cost-effectively vs hiring a few more people?

Obviously. It was the goal of automation since its inception: reduce human involvement.