This is going to be the norm across the board as the models have failed to live up to the hype.
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)
> 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.
> Mistakenly we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that that would produce a high-quality product.
Clearly a lot of careful thought went into their strategy of using AI and firing engineers.
How interesting. So a Ford car is now more reliable than a Toyota soon after purchase but Toyota didn’t fire anyone and Ford fired, implemented automated reviews, and rehired. So their process didn’t bring them back to neutral. It placed them above the traditionally reliable manufacturers.
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.
Setting aside how shortsighted it is to fire your employees to replace them with AI, Ford also screwed up by firing the wrong employees. LLMs work best in the hands of experienced senior engineers who can work at a high level of abstraction because they already understand all the pieces underneath.
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.
> 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.
aye.
I've posted this here at HN several times but I had my intern try to track down how many CVEs from a list of vulns we found were being exploited in the wild -- couple years ago, pre mythos that is. I also took the list to Copilot and Claude.
All 3 got different answers, albeit off by one or two. The intern told me at least he didn't know about X, which was far more useful. I later had him whip up a plan and some basic code to patch some of them, and the experience comparing his answer to Copilot was similar to before as well -- both mostly worked, but didn't, and in different ways, and mostly due to not knowing institutional best practices.
Even if they only fire the juniors and retain the seniors, they have effectively broken the pipeline that creates more seniors for the next few decades.
That is either betting on AI being better than humans then, or closure of the company.
350 of how many laid off? If 350 is a fraction of the total replaced with AI that's going to be counted as a win for AI reducing costs, they just were a little to ambitious with the initial round. That'll be counted as a learning experience because we're early in the replace people with unintelligent tools process.
This is exactly the idiotic use case of AI coming back to bite them.
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…
This just feeds a certain narrative and allows people to take exactly the wrong conclusion. Just because there’s some uncertainty at the edge, it doesn’t change where things are going.
This HN headline is editorialized, the Bloomberg headline is "Ford AI Hiccups Push Carmaker to Rehire ‘Gray Beard’ Inspectors".
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.
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.
Interestingly, there were no consequences for the execs that made this 'mistake'. There seems to be almost unlimited cover for execs cargo culting on using AI as a pretext for layoffs. If it doesn't implode almost immediately, they get massive bonuses, if it blows up in their face, oh well they had the courage to 'take a bold strategic decision'
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.
111 comments
[ 4.1 ms ] story [ 107 ms ] threadAnd 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'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.
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.
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.
aye.
I've posted this here at HN several times but I had my intern try to track down how many CVEs from a list of vulns we found were being exploited in the wild -- couple years ago, pre mythos that is. I also took the list to Copilot and Claude.
All 3 got different answers, albeit off by one or two. The intern told me at least he didn't know about X, which was far more useful. I later had him whip up a plan and some basic code to patch some of them, and the experience comparing his answer to Copilot was similar to before as well -- both mostly worked, but didn't, and in different ways, and mostly due to not knowing institutional best practices.
That is either betting on AI being better than humans then, or closure of the company.
It's OK to just say that the plan was to rehire back the engineers for far less compensation.
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…
"Welcome back, you are now two levels down"
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.
It’s a disease that has spread throughout all of capitalism.
But that’s USA 250 years.
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.