Ford AI hiccups push carmaker to rehire ‘gray beard’ inspectors

Corp CEOs / CFOs golf buddies coouldn't stop yapping about how much they saved paying people less by offshoring. So step 1, they fire a bunch of people and send work overseas, driving up their financial metrics for 5-6 quarters until their staff and their organization finally break at stage 2. Turns out cultural and communication barriers are things we haven't really figured out how to communicate across efficiently, and that only a handful of people are truly rockstars at it; others just aren't cut out for it. Stage 3 anyone that is competent to get another job already left, leaving a smoldering shell of company that dies by attrition at stage 5.

In a sense, using an LLM agent is like providing instructions to a very smart, very quick junior who despite being brilliant has some blind spots and lacks institutional knowledge. That's something that seniors excel at, so by firing your seniors you've fired the people best positioned to make full use of LLMs.

A company with 1000 employees that builds 100 houses at a time might cut a dozen employees to create three robot crews. A 10,000-employee company that builds 1000 houses at a time would still only need to experiment with a handful of crews, affecting only 20-30 or so employees.

I marvel that a company has let themselves grow so out of touch with their business that they can't understand the impact of changes without carnage at this scale.

This has nothing to do with LLMs and instead is almost certainly about their MAIVIS and AiTriz pilots, which use old school CNNs on custom IBM hardware to do visual inspections.

And the verge is covering it too:

https://www.theverge.com/transportation/956316/ford-quality-...

I do think LLMs and agents and all are great at helping you through tough problems but we aren’t there yet on getting them to do all the work while we just architect and design. Again, it’s close, and for your use cases you might be there already but for low level and big corporate lift and shifts, it’s not there yet.

I have agents, agents of agents, and I still find myself having to carve big chunks of my project off and feed it to the dogs because it’s garbage code. (GLM-5.2)

I think companies would more careful about how fast and lose they operate, if firing may mean having to contract with a 3rd party.

I can see a lot of companies coming to this realization over the coming months and years.

If I hadn't already landed a job somewhere else, I would only return with a 20% pay bump and an iron-clad contract.

AI is confidently wrong a lot. And so you can imagine a lot of execs thinking the AI can do a lot more than it really can.

In other words, they don't really have a plan, but they are happy playing with people's lives via layoffs, since it's the 'in' thing to do. The incentives are huge on the upside and zero on the downside for them.

"Welcome back, you are now two levels down"

I no longer want to make connection with any coworkers.

So maybe the key is firing everyone and then rehiring the good guys after you implement automated systems.

Though I’m somewhat surprised. I didn’t expect Porsches to top a reliability measure. I thought they were in the “fancy but unreliable” bin. Interesting.

The editorialized headline is also misleading: "Ford rehires 350 engineers after AI fails to preserve expertise or train juniors" - there is nothing in the original story that suggests Ford were expecting AI to "train juniors".

And since the Bloomberg headline is behind a paywall the editorialized headline is most of what we have to go on.

This Verge story would be a better link: "Ford had to hire back former engineers to fix mistakes made by its automated systems" https://www.theverge.com/transportation/956316/ford-quality-...

And the crucial detail: nothing indicates Ford laid off the 350 people who were re-hired. It looks to me like it could be bringing back people who retired.

The short sighted gains (and I’ll assume that they are chasing quarterlies as usual) are to be had by firing most of the junior engineers, keeping the seniors because with AI they can n* their productivity.

Basically you can fire 2x junior engineers for every senior engineer you keep. But the senior engineers are the keystone here, and without juniors eventually becoming senior engineers you’ll eventually be screwed.

But, that’s a problem for the -next- c-suite gang… so…

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.

Clearly a lot of careful thought went into their strategy of using AI and firing engineers.

I would rephrase it as it’s only as good as you know what you are doing. Even if the trained input is good, keeping it to scope and making sure it delivers without workarounds requires a human brain who have the past experience.

won’t someone think of the lightcone!

It's OK to just say that the plan was to rehire back the engineers for far less compensation.

It’s a disease that has spread throughout all of capitalism.

But that’s USA 250 years.