[stagger87]

> The return of the veteran engineers at Ford cuts against the prevailing wisdom — and fear — that AI will replace all kinds of knowledge workers. But Ford found the machines couldn’t replace experience.

I'm not sure this story is illustrative of that, when you have a VP of engineering saying “Over prior years, we didn’t pay as much attention as we should have to the experience of our most knowledgeable engineers that have been with us through many product cycles.”

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.

[rapind]

> 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.

[neilv]

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"

[teiferer]

Is there any substantial number of companies actually training AI? Or do you count writing skills files for Claude as "training"? (Cause it really isn't..)

[boutell]

We all know what you mean. But doing what is necessary to make the overall automated system more autonomous = training, at this 30,000 foot altitude.

[teiferer]

Well for grandma on the street I can accept that, but shouldn't at least the tech community be more precise in terminology? "AI" is also a misnomer. So many things in our industry are that it always takes some layers of digging in a new area to understand what they actually mean because the words have shifted their meaning.

[neilv]

I intended for the entire sentence to be in terms of the thinking of top leadership.

And to gloss over how that improvement would actually happen. (Not knowing what they've currently done and want to do, but for example, guessing: probably in partnership with vendors, consultants, etc., iterative and experimental process and tools improvements, and involving a variety of approaches and refinements.)

[Chaosvex]

Ray tracing says hello.

[makeitdouble]

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

[jvanderbot]

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?

[red75prime]

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