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AI is pretty good at scaling existing knowledge, but if the actual knowledge is just in the head of an engineer who can hear that a press is acting up, the model doesn't really have much to go on
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.
It doesn’t take long for the cracks to show:
- Not enough program/project management.
- An intuition that service dropped but no good metrics.
- Retrain the outsourcers after the first team quit.
- Inability to size new projects.
- Shadow IT departments form in the business units.
- The outsourcers don’t care about things like vendor consolidation or holding other vendors feet to the fire.
All of this might still be worth it if it’s done strategically to improve a chronically underperforming IT department. It’s rarely effective when rushed to cover up poor performance of the core business.
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.
>Over the last three years, Ford says it has hired 350 veteran engineers, many of them former employees and others from suppliers
And not all former employees were laid off. Senior 'greybeards' have many job opportunities elsewhere and often leave for better offers.
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)
It’s human in the loop over and over again tho
Some might hate that writing code (which they enjoy) is turning into that, others might doubt the efficacy of doing that and the claims about it working so well.
Personally, I’d say that docs help as long as they’re meaningful and not too long (even AI tools have limited context), but you probably also want to codify what you can into code.
For example I wrote a tool in Go and goja called ProjectLint (not public yet but anyone can do that in a week) where you write custom rules in regular ECMAScript that can check whatever you want - code conventions across languages, project structure and architecture and all the stuff that goes under “In this project, we do X but don’t do Y” that just telling an LLM about (or colleagues) will be worth nothing (even memories and focus are limited), instead CI gates that.
I guess I reinvented a simplified and stack-agnostic version of ArchUnit but whatever, it works for me and I can use the same tool in Python and Java projects and elsewhere as well as parallelize all the read only checks and run sequentially the potential-write ones that might auto-fix stuff.
For me, my human only productivity in the firmware work I do is usually around 100-500 loc a day on good days. Obviously more when clean-slating the initial work on a project , but that’s typically a day or two and the same ratios apply.
With ai tools, I roughly 4x that with the same effort, or 2x it working lazily from my phone playing with my 2 year old.
The code is typically also more compact so the LOC metric is strong here IMHO.
Overall I have about the same number of bad-unproductive days, far less bugs (but worse bug hunts) and 10x better documentation lol.
Coding is definitely a different job though.
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.
I don't know when the "MAIVIS and AiTriz pilots" you mention were implemented but another possibility is the Ford PR team saw that 'AI Backlash' stories are currently trending and opportunistically focused on that to explain a positive news event which likely had many causes. IMHO, we should view these 'AI Backlash' themed stories as no more valid than the 'AI Downsizing' themes they previously seized on to justify layoffs they wanted to do anyway.
First day on the internet propaganda-discourse machine?
If the article doesn't support your preconceived biases that's no problem, assume the title is true on it's face and comment reinforcing it. If neither of them support you then attack them. Welcome to internet comment sections.
Submitters: "Please submit the original source. If a post reports on something found on another site, submit the latter." - https://news.ycombinator.com/newsguidelines.html
(We've reverted to the article's title now)
p.s. Article titles are sometimes rotated by the publications, in which case the submitter usually followed the guidelines but it takes time for us to catch up.
I don't have high hopes that there exists a bulletproof solution to this.
It's a model of language, yes? Trained on a big corpus of text.
I have read a lot of stories and accounts in which people were told not to do something and inevitably they did it. Like, lots. Far more than stories and accounts in which people were told not to do something and they then didn't do it.
If I'm reading a story or account of something, and it's really hammered home that they've been told not to do something, it's kind of inevitable that they will then do that. I'm not even an LLM and I noticed that's the way these things usually go.
So is an LLM just doing what it's been trained to do? Sometimes in the stories and accounts, there's a whole lot of time and tension before the bad thing happens, but that's just part of the fun.
These are no general purpose machines. They are shipping a subset mindset not general intelligence like they want us to belive .
He valuations of a bunch of AI unicorns disagree.
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.
You just want to make sure you have it, and not your boss using it against you.
How many tens of trillions of capital have been incinerated in reducing the quality of life for workers compared to actually uplifting them?
But this is difficult to implement since AI doesn't have a body to follow someone around and it would take immense amounts of compute to do so using telemetry and cameras. You would literally be spying on employees 24x7 for weeks at a time with the express goal of replacing them someday.
https://books.worksinprogress.co/book/maintenance-of-everyth...
If I hadn't already landed a job somewhere else, I would only return with a 20% pay bump and an iron-clad contract.
I would recommend IT/server administration as that is a constant business need, if you prefer stability with more limited upside.
I can see a lot of companies coming to this realization over the coming months and years.
I think companies would more careful about how fast and lose they operate, if firing may mean having to contract with a 3rd party.
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.
That said, this application of AI was profoundly stupid from the outset. You don’t necessarily fire people for a bad result from a reasonable decision making process, but you do fire them for poor judgment and reasoning. There’s nothing that can fix that except for not letting those people make decisions anymore.
Which I guess is getting at another thing. The failure was predictable. People shouldn't be rewarded for failing to avoid obvious predictable failures. Maintaining their status quo could also be seen as rewarding them.
I can't speak for how these particular executives were handled. I've never worked at a place where people were quickly fired for mistakes unless it was something extreme. It's usually based on track record rather than a single thing. Most employers understand that if they fired people for making mistakes they would run out of employees very fast. On the other hand, someone who learns from a mistake probably isn't going to do it again so you may have a better employee than a hypothetical replacement. It's also generally understood that people with a large scope of responsibilities have a large blast radius when things don't work out. It just comes with the territory and it's not exclusive to the executive suite.
Workers get fired when they are wrong at much smaller scale, why not these people? They are not special, they are simply lucky and connected.
https://news.ycombinator.com/item?id=42639566 ("Pharaoh must signal, to shareholders, to a board, and to their peers. There will be no consequences for failure to adhere to this proclamation.")
Salesforce will hire no more software engineers in 2025, says Marc Benioff - https://news.ycombinator.com/item?id=42639417 - January 2025 (390 comments)
https://www.salesforce.com/company/careers/jobs/?search=soft... (724 results, as of this comment)
That's why I'm saying to separate the process from the result when determining consequences. Someone who consistently exercises good judgment and who makes well-reasoned, thoughtful decisions is likely to achieve good results more often than someone who doesn't. But, event then, some things just don't work out and it impacts people's lives.
I would absolutely fire those idiots at Ford though. There's nothing wrong with trying to leverage AI. Personally, I like AI tools and I rely on them daily. But if someone lacks the judgment to figure out when a job should be performed by a human then they shouldn't be able to make decisions about how to use AI. These people are clearly out of their depth and just faking it. Clown show.
riff-raff cogs get fired for making bad decisions all the time. also if not punished for making decisions. how do execs ever get punished because all they do is make decisions.
As usual it's communism for the plebs and something entirely different for the capital wielding class.
Nobody should "sacrifice future career prospects" just for a job. And if they do, it's hard to blame the employer on this, especially considering the premise implies they had choice in the matter.
Bad example. Ask Bezos how much he paid his wife after the divorce.
And why does the board/shareholders allow a CEO to continue into their position by just following everyone else?
I'm sure things are different at massive scales, but I run my own side business (photography). I watch the local market, and I have the attitude of "Whatever everyone else is doing, I want to do the opposite." and it's worked for me so far. The area doesn't need yet another "dark and moody" photographer with boring sepia edits, blurry photos with a film preset, and the same exact font and colors on the website as everyone else.
You don't become a pioneer in your industry by just cargo culting everyone else. It's low effort leadership and if I were on the board it certainly would not inspire my confidence in their ability to run a company. You're telling me not a single person at the table asked "Do we have these engineers' institutional knowledge documented somewhere before we fire them all??"
the same consultants can be blamed if decision backfires
Leadership made a decision and that decision was bad. This happens all the time, including allocating budget for staff. Any effective organization is going to judge the outcomes of these types of decisions and it's going to come up in performance and hiring. If this was an isolated situation then possibly they won't fire anyone over it. But you really need the context to judge whether the response was correct.
Wasting company resources and making the company look bad in the press won't be rewarded, and that includes at the board level to the CEO.
Even if you categorize missing out on some bonus or something as a consequence, it pales in comparison to the damage they've done and the lives they've severely disrupted and possibly irreparably damaged by firing people on a whim. (And I consider firing people because you fell for the AI hype / obvious marketing to be a whim)
It sounded like they had a "Stellantis discount" for people who said something.
Nice guy, actually.
The retention rates before COVID are back, and companies have way more people than they might need, that's the real reason so many places have started to slash, but blaming AI is easier.
https://en.wikipedia.org/wiki/Great_Resignation
Kind of made sense to me, I saw some of those outcomes happen in a former employer as well, they had an influx of income during 2020 that was not going to stay around forever (restaurant industry).
One for lay-offs, because it was the best move at the time with the knowledge they had.
Second for quick correction, ability to pivot and execute quickly.
It's been always like that
Because we've been alive in America long enough to see this cycle thousands of times. The execs rarely face the music for bad decisions. A round of layoffs looks like a failure to us, but to the investors it was a good idea that didn't work out so there's no punishment for trying to save money.
It is reasonable to assume, that this could be walked back in such a way that no one is held accountable.
Are there any recent documented instances of executives being punished in some level of career-affecting way for bad performance?
Even when they get fired they get golden parachutes.
Example: Sam Altman founded a complete failure of a location-based social network, where the board tried to remove him twice, lied about being chairman of the YCombinator board, and now gets to be CEO of one of the most valuable companies in the world where the board tried to remove him as CEO once.
Failing up is very common in our corporate system.
The article makes no such claim. What is your source? Absence of evidence is not evidence of absence. Or, are you just making things up that you believe are likely, like an AI would?
If you say something is illegal and costs $X as a fine, you don’t curb behavior, they just bake the fine into their business model.
Sometimes things don’t work out. That doesn’t mean it was a punishable offense to try.
reading this article I think that is not what happened in this specific case:
> Over the last three years, Ford says it has hired 350 veteran engineers, many of them former employees and others from suppliers, to help address seemingly intractable quality woes that have cost the automaker billions.
> “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,” Poon said. But “we recognized that for us to enhance some of our automation and machine learning and artificial intelligence tools we needed to ensure that they were trained by the most experienced individuals.”
That is, Ford had been slowly relying more and more on automated tools (if the "rehiring" is over three years, then this all precedes our current "AI" ecosystem) and realized that now that they want to add modern AI tools, they need experienced engineers to train the newer systems, and are hiring people from the open market, where some of these folks were former Ford employees, but nothing like "were laid off due to AI".
That is this doesnt sound at all like "Ford fired 350 engineers to be replaced with AI and is now backtracking", which is certainly what the headline here implied.
Risk is inconvenient to shareholders, who also happen to be the people with the most political power in the US. They're:
1) retirees living off a pension/retirement fund backed by shares of companies like Ford
2) investors who have plenty of money to ~~bribe~~ donate to political campaigns or
3) C-suiters put in place by the other two groups who are compensated primarily in shares.
These groups are all incentivized to see the risk to their income streams minimized as much as possible. Show me the incentives, and I'll show you the outcomes.
Thus, we got rid of the risk.
Their entire management skill involve the application of one of the following options:
1 - Fire People
2 - Spend Money
3 - Call a meeting
I'm prosperous because god/market deems me worthy.
It reminds me of the conspiracy theories I would hear as a child along the lines of powerful people running the world in shadows. I certainly feel like the ways people like executives keep getting away with unethical and in some cases illegal behavior is there's forces in the shadows supporting their behavior. I was told in history class that throughout history when such types of people arose such as kings in France or massive dictators who conquer countries, that the "good" or "masses" of humans eventually over throw them - well here we are and why isn't that happening?
I see instead a class of people weak, afraid, and defeated and continually asking others "why aren't you doing anything" without the awareness to see "You are the one who is supposed to do something" edit: applying this to myself, I'm certainly trying. Before I was fired at Capital One (as an engineer) I would continue to ask tough questions of integrity to executives and my team and managers, things about integrity, things about inconsistencies in our stated values and how we were actually delivering work. I took some heat, was not very liked, and took continual abuse from my team until I was eventually kicked out. I am happy to share how little I noticed people who felt uncomfortable with team culture and executive communication were just silent and afraid, and in denial as I got attacked and abused by management.
We already do with legislation that requires severance packages and tax benefits for hiring. Many countries go much further.
One might bring up the personal consequences bourne by surplus employees who're then laid off during the unavoidable corrective phase - or is that not something society should care about? What are you optimising for?
> There’s no reason we couldn’t decide that we want to err on the side of employing too many people.
Yeah that's not how a company should run.
Don’t blame a customer for the vendor’s irresponsibility.
Just because I would not be destitute tomorrow does not mean that my life (and those of my family) would not be deeply impacted.
1) you can only get promoted if the company grows and/or someone above you leaves, or dies, or ... Btw it really requires leaving permanently. They leave for 10 years due to being in coma after a traffic accident? Nope.
2) the oldest person gets promoted (and that means ancienneté: longest in the company). No arguments, no exceptions. To the point that there are plenty of teams that have a manager (who gets the 10% pay boost) and an actual manager (who makes things work). Often not the same person.
3) No mobility (technically, yes, there's mobility, BUT your ancienneté resets in many cases. So it's really stupid to do)
They are often both illegal and unenforced. Your old employer isn't going to waste time hiring a private detective to track down every former employee's new work place that you didn't include on LinkedIn.
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.
"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.
An expensive process.
It's just so strange any other profession have unions or bodies that protect their job against this sort of practice.
if software devs were lawyers then AI would've been banned
If the company tries to layoff 10% "due to AI" the remaining 90% can strike.
History is full of union solidarity vs idiotic management.
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.
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.
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"
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
Clearly a lot of careful thought went into their strategy of using AI and firing engineers.
C-suites completely disconnected from reality and assuming we've already achieved ASI/AGI, and marketing teams & business journals are only furthering that narrative.
It's so weird. I don't know what it is about AI that causes people to throw all thought and caution to the wind and charge forward blind. Its like they've been chomping at the bit for decades to get rid of those pesky humans and are so hyped up over it they can't see clearly anymore.
These guys have squeezed out every cost and slack from their system. They've found the exact revenue-maximizing prices and segmentation for their products. They've cut quality to the point where customers will just barely not reject their product. They have used every legal and accounting trick at their disposal to keep that line going up. But, next quarter, line must still go up!
The final massive cost to cut are all those damn human bodies that they they still have to keep around. They've driven down salaries and benefits to the minimum they can get away with, and they've extracted the maximum value from employees they can. But they haven't figured out how to get rid of them entirely. They are staring down the barrel of the gun and just can't see a way to cut this cost further. Now, magic AI comes along, and everyone is saying that the black box can replace those bodies. The C-suites believe it. They have to believe it. Line must go up! This is how they'll do it for a few more quarters. This is why the messaging is so unified across the industry, across every C-suite out there. They all need to believe.
The real danger for the economy is when the runway finally runs out. And I believe we are at a perfect-storm scenario... AI is obviously a giant wash-trading bubble that alone would be sufficient to trigger a repeat of the 2007ff crisis. But on top of that, we got the issue you mentioned, i.e. everyone running out of kool-aid and noticing it too late, with no easy way of turning around, and we got the war risk and supply chain shocks thanks to Iran and Russia, and and and.
It's just a hype cycle. In my 15 years in data, I've seen around 3-4. Every time leadership get way too invested in the possibilities, and they waste tons of money on doomed efforts. A good example of the prior one was "Big Data" which was even more pointless than the current AI boom.
Don't get me wrong, there is valuable tech there (at the very least, being able to reliably generate structured data from unstructured input is incredibly valuable in data), but the current hype is way off the charts.
For those that lack initiative, strategy, a real understanding of their business, engineering, etc., the spewing words is the whole thing. It overshadows their entire understanding.
What does hype even mean concretely? I think this is just a coping mechanism if you ask me.
My favorite theory about this is that we're all used to "speech == intelligence" and now that we have something that can produce coherent speech, it seems like it must be intelligent to people who don't know how it works. Even people who know how it works still anthropomorphize it to a weird degree. So a business person sees this thing that's both intelligent (to them) and superhumanly fast and it seems like the ultimate silver bullet.
1. Zero personal risk because cargo culting is a valid excuse in Executive World. If investors are on board, its good, no matter how stupid or destructive it actually is.
2. Top leadership's friendship with the country's leadership equals access to cheap debt financing since money is all fake and generated out of thin air
3. Too big to fail
> Its like they've been chomping at the bit for decades to get rid of those pesky humans and are so hyped up over it they can't see clearly anymore.
This is precisely it. Here's my analysis:
AGI is a savior figure for the capitalist class. A tech version of the Second Coming, delivering them from the pesky demands of workers, like a living wage or (gasp!) sick leave.
That's why they're all so obsessed with it, it has religious-ideological component to them. When you hear them talk about AGI, there's always this weird eschatological vibe with it.
Unfortunately, they're blinded by their beliefs and can't think things through even one step further. Even if their cyberjesus comes down to them through the machine and replaces all workers, who's gonna buy all their stuff then?
All they're doing in their capitalist zealotry is ringing in the end of capitalism.
Knowledge or skilled workers can be used by the AI for swarm training data generation; what value do the execs have to AI?
I think the most beautiful part of capitalism is selling elites rope to hang themselves.
In that order, apparently.
Step 3: Rehire key personnel at lower cost than whomever was fired in Step 1. Step 4: Take credit for cost reductions . . . and give yourself a raise!
Step 1: 30 minute conversation with AI on how to use AI. Step 2: fire everyone.
My point being, Ford's had shit for brains for decades. Its a fucking wonder any of their vehicles make it out of the parking lot.
That made reading their subsequent layoff blog posts pretty depressing
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 headline gives the impression that Ford fired 350 engineers and tried to get AI to train the replacements and then re-hired them when that didn't work.
That impression is false, which means we're wasting time having conversations about it.
(The top comment thread on here right now - https://news.ycombinator.com/item?id=48674446#48675092 - starts with the assumption that Ford execs made the mistake of laying off 350 people and then discusses if they got good severance packages etc. - here's the best comment I've seen calling that out so far: https://news.ycombinator.com/item?id=48674446#48675486)
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.
It's OK to just say that the plan was to rehire back the engineers for far less compensation.
won’t someone think of the lightcone!
It’s a disease that has spread throughout all of capitalism.
But that’s USA 250 years.