Get ready for this to become a common theme. Boardrooms are still engaged in the fever-dream promise that AI will solve all their problems, particularly those involving pesky humans. The simple lesson of "AI is another tool" will be a hard-learned one. Some industries, such as software, will take more time to mop themselves into a corner before they discover that velocity should never be a first-class concern. Speed should only come as a side-effect of quality.
Nah, that’s the future executives problem, the current executive gets to brag about how their AI integrations cut costs while maintaining an acceptable yet enshittified quality
You seem like a person who works at a place that doesn't have an AI mandate. That sounds nice. I miss when we had nice things in the world like that. I will never take that for granted again.
He's just making a general "efficient markets" argument. He's arguing that whatever happens in a couple of years will be the right thing, no matter what is happening now.
That is essentially not an argument in any direction.
If it works. Where is this 100x software output? I just see more AI tools to check it does not derail, but where is the actual software revolution, where all developers are fired? I'm still closing AI PR slop here
If it is 100x anything more
interesting than line count, it will be micro-projects: Local barber wants a new website. Architecht wants to put their own plan into a numerical physics simulation library someone else wrote that has its own syntax. Schoolkid wants a customised word puzzle app for the foreign language they struggle with. They couldn't possibly code it themselves, but they can check what it is doing.
Trust without verification though, we're waiting for AI's
Challenger disaster equivalent.
I'm not going to speak to the output side of your comment, but yes, developers are being fired over AI.
> The latest layoffs across all tech companies.
So far in 2026, there have been 421 layoffs at tech companies with 157,807 people impacted (882 people per day). In 2025, there were 783 layoffs at tech companies w/ 245,953 people impacted (674 people per day).
It wasn't meant to be a literal statement, more just a reflection that the situation is so bleak that I cannot imagine a better future; anybody expressing even a little bit of it seems to me like a somebody who has not been crushed into compliance through force.
Quoting the host of the recurring Quiz Broadcast sketch from That Mitchell and Webb Look: "Books mention 'hope'. What was 'hope'?"
AI mandate is one of the best things that's happened to me. It's the easiest metric to game in the world.
At one point my boss asked why my AI usage was lower than other team members. I instantly knew what to do. Every session is now run at ultracode effort. My automated PR review bot averages like $80 in usage per PR review.
It is extremely easy to burn tokens if that is required.
Explore this codebase.
Team x wants y feature, research and generate a full plan.
What does feature x in codebase y actually mean?
Analyze code coverage in x.
Map out code flow and find concurrency bugs in y
and on and on...
Oh and my favorite: Use 5 independent subagents to review code change and summarize the findings, and for any finding determine if they are real concerns
The other day claude spun up 100 agents and took an hour to type 30k token document to tell me something was impossible to do. I googled it, found a pr on the 3rd link that showed it was possible. "You're absolutely right!!"
And the planet... While I experience some schadenfreude when reading these comments from programmers, I also can not help to wonder when this insanity will this end.
There's nothing people run out of faster than other people's money. I expect this second half of the year we see that the cracks in the AI business grow and bring the whole thing down.
Just a bit after anthropic and openAI unload the "value" of their companies into retail investors.
> I also can not help to wonder when this insanity will this end.
When AI use starts to be a line item cost on public companies' financial reports + Anthropic and OpenAI have IPOed and have to file financials too + they kill their growth-hack monthly all-you-can-eat plans.
The entire house of cards falls down when the success metric shifts from "Are you using AI?" to "What return value are you getting for the money you're spending on AI?"
Some smart companies / departments are going to be able to demonstrate stellar AI ROI, but I'm going to be shocked if the bulk of current demand isn't revealed to be naked. Mostly because middle management is always stupid about adopting and using new technology.
> I also can not help to wonder when this insanity will this end.
AI companies are running out of money to subsidize those queries, and worse are needing to show a profit. All while they are having a harder time to raise more money as investment.
If nothing changes, things should become more rational soon.
... now... IMO, I place the odds of nothing changing very low...
There is value in doing all that too, though. Admittedly with strong diminishing returns, but it's there.
Eg by doing that I was able to develop non-essential features which increased our quality of life for devs last month without going through our PO who'd need to price it - because that does let's you create changes in an incredibly hands off manner with miniscule amount of time investment if you already know what you want to achieve, and how the end result should be...
Admittedly, that's a pretty narrow usecase which is rarely the case- but if it is...
And the more uselessly amusing thing is that the manager who requests higher tokens usage probably also doesn't care whether it's producing slop or not. Metric goes up; managers happy until CFO is reported income hasn't gone up as quickly as costs, and that makes the CEO optimistically concerned. Never expect underlying thought from a messenger.
It's interesting that LLM barely had any vetting period or experimentation phase. Suddenly everyone was supposed to test it in production, it seems.
Afterwards, give me 5 separate documents with 10 plans each for how to implement this. Triple check your work, make no mistakes. Then give me 3 distinct executive summaries emphasizing different areas.
Let us not forget /ralph-loop “explore the codebase for bugs, write tests for each bug found but do not fix the bug, only capture its existence in testing” will ensure your agent never stops burning tokens.
I am of a particular disposition that makes it difficult for me to do lie about my work, especially if I were in a firm where people are reading my chat transcripts. As much as I want to stick it to The Man, it feels a lot better for me to just say "no" and burn through my 401k until this blows over.
I'm not too proud to admit that this whole thing scares me though. I fail to see how anything will get better.
Congrats, you have a moral compass and you sound raised by good parents. The other people in these threads bragging about burning tokens, not so much.
I’ve sadly had the same thoughts lately to cash out my 401k and say farewell to software development. I’m hanging in for a little longer, I think the AI/greed fever breaks sometime soon (months not years).
It's even worse/better. It's corporate financial malpractice. At some point they will wake up after the AI psychosis dies down. That might take 1-2 more years. After that most companies will realize that AI is a tool, as OP said, and adjust budgets accordingly.
Importantly, "adjusting budgets" here is for most companies, you know the ones you have to fight to even get an IDE license, a euphemism for zeroing the budget.
Hello, I am from a company whose IT leadership that saw this silliness 3 months ago.
Yes, all developer-focused AI subscriptions have been cancelled, and only AI features tacked onto existing subscriptions are part of the AI strategy (eg: Jira+AI, Confluence+AI, Analytics suite du jour+AI, Microsoft Copilot Pro (SHUDDER), etc etc etc.)
Yes, it is virtually impossible to get any additional spending approved.
Yes, there is no more Claude, there is no more Codex, it is all gone now. The AI hype occurs only in company-wide emails about commitment to modernization (with AI), reorganization (with AI), and consolidation (with AI), where no actual strategy is proposed other than what the management consultants advise (with a caveat that there is no budget for anything other than AI features that are tacked onto existing subscriptions at no additional cost.)
If your manager is asking you why you aren’t hammering 500 nails a day with your company hammer under threat of replacement, you’re going stop worrying about the surfaces your driving nails in to and simply start swinging.
1. It is not comparable. Idk the environmental toll of 500 nails, but tokenmaxxing definitely has one. Especially when it doesn't have any provable and substantial benefit.
2. Your responsibility doesn't end because your manager says so.
3. It's not just about the employee who actually burns the tokens, but also about the rest of it: the idiocy up to the top, and the irresponsibility of the companies offering the service.
> 1. It is not comparable. Idk the environmental toll of 500 nails, but tokenmaxxing definitely has one. Especially when it doesn't have any provable and substantial benefit.
Then pretend it was 5 million nails a day from a newly invented nail machine gun. This also has no provable and substantial benefit. Build a house that way and it will quickly be more nail by mass than everything else combined.
I don’t disagree. The point is capitalism operates entirely on incentive to keep our jobs or die on the streets. If they say “use all the nails or you lose your job,” people aren’t going to care about the waste or broader costs. Nails, AI, choose your example. It’s the same result unfortunately.
The point about capitalism isn't really accurate. Communism had the same problem. It's more about greed and power, and a system that sustains it than about the ideology behind it, I think. However, their ideological opposites, anarchism and liberitarianism, offer false ways out, too, as humanity is simply not capable of sustaining that.
I'm sounding a bit like a broken record, but the only political system with a proven track record in modern society is still social democracy: educate the people so they don't bash each other's heads in, distribute wealth and power better, and regulate the markets. It unfortunately died through the unholy matrimony of material well-being and social media.
The reason I’m saying capitalism is because the context is employment + the US. In the US employment is everything. It’s social status, it’s the roof over your head, it’s healthcare, it’s your identity.
Similar issues exist in communism too. It doesn’t mean you can just go “but communism” to dismiss me when I raise an accurate and valid critique of the system Ford operates in.
It wasn't meant as a riposte or anything. I just didn't read "capitalism" as "the system" but more as "the root cause" and hence what has to be changed.
I'd unironically like my workplace to cover AI spend for me.
There's so, so much mechanically simple but time consuming refactoring that should be done but nobody ever does that because there's never enough free time. Or even various utility scripts and at least finding out of date docs (or writing very basic ones where none exist, though it'd be hard to get them not to feel like slop writing). Or figuring out what additional custom linter rules would be useful, how to improve the CI pipelines and so on.
If I had the Anthropic Max 20x subscription, I could make a large part of the technical backlog disappear (relatively safely).
I've had great success with OpenCode Go and DeepSeek v4 Flash for Terraform code refactorings and extensions. It's cheap enough to pay it yourself ($5 first month, $10 afterwards). Ideally you provide the model a feedback loop (e. g. passing tests) so it can safely iterate.
There will always be more work to do, especially for someone else's company.
What's the rush? Friday will still come at the same speed, and it's unlikely you will receive an increase in pay to account for your increase in productivity.
It's also the easiest way to determine if your management has AI psychosis or not, and make corresponding decisions about whether to stay with the company.
as a CTO, its been crazy pushing back against these AI mandates. Almost always from VCs and non technical contributors. I'm pretty liberal about using AI but it has its limits. I think of them like swim fins. you can dive much deeper with them but if you didn't earn that ability, you can find yourself too deep to get your next breath of air. likewise, its important to never let the ai do work more than one ring outside of your knowledge base lest it do things you dont' understand and therefore can't audit.
It's not unreasonable to mandate that one should try it for some of its safer uses, or to spend time teaching people what the good uses are, which keep growing... but mandating a significant part of the day-to-day is telling employees they have no agency in how they achieve objectives. For people that aren't technical, it shows they aren't good at the social either.
The company I work for, thankfully, is a bit like that.
The AI initiative there is a lot more in "let's try to find ways that this can be useful" instead of "let's use this to the maximum extent".
So far it has been a mostly positive experience. We could figure out ways where it saves time instead of burning money in a token pit.
The only downside is that code reviews are becoming the bottleneck. Every PR still needs a human reviewer, and that is not changing. The influx of PRs increased slightly, the rate of reviews not as much.
No doubt, but the issue I think they keep running into is they don't understand how useful those "human tools" are, so they keep trying to replace the functions humans provide with AI, without realizing all the other functions that the humans also provided.
Marx had a way to think about that. He would distinguish between labour as in generalized socially necessafy labour, and specific skilled labour.
Value is measure in generalized labour, since that the universal measure of human effort. The genealized amount of time a human being must spend to produce something from its parts. Generalized labour is also what's bought from labourers. You don't pay them to do something specific, you pay them to labour in general.
This contrasts against specific labour, which is whats actually required in the moment. Generalized labour power must be the right kind of specific labour to actually produce anything of value.
The AI leaders have been told that AI is labour. To the extent that it currently is, which I believe is only the case because the market hasn't adjusted, it's not the right specific labour to male anything valuable.
I find this comment, on it's face, very hard to understand. An apparent abundance of qualifiers without definition. Is this an example of circular reasoning?
It seems to me that the text is saying that generalised labour produces value, but then only specific labour produces actual value. What is the difference between actual value and value in general? Is some value somehow more valuable that other? Are we even speaking the same language? Is this just making shit up as you go along and hope nobody notices because the general idea is appealing?
My partner had booked a table for lunch for us and our friends. Six adults and six children. One of the couples had forgotten a party earlier that morning, so we tried to move the booking a couple of hours later.
Unfortunately the only phone line was answered by an AI bot who stubbornly refused to move the booking, simply telling us there was no availability within an hour of our booking.
Fortunately my partner was passing so was able to go in and speak to someone is person who was happy to move our booking back 2 hours. Lunch and drinks for our party must have come to several hundred pounds.
I'd estimate our party was between a third or maybe half of all the customers there. Had we chosen to book elsewhere I bet someone would still be patting themselves on the back about how clever they were to save a few minutes a day on actually answering the phone to actual customers.
It's the conceit of capitalism. We've structured our entire society around giving the boardroom class most of the rewards from our societal output, so they've taken that to mean they create most of the value. They are job creators, deliverers of technology, builders of nations, and how it gets done at the low level is an fungible implementation detail. Whether it's slaves or workers or robots down in the fields / mines / factories, the board are the ones driving the ship and therefore doing the real, important work.
And yes, this does mean they view us workers as somewhere between slaves and robots, replicable by a token predictor.
I wish I could work somewhere where I’m _marginally_ less subject to the whims of the Boardroom class.
I’m sure they’re having a great time, and getting filthy rich doing it, but I don’t enjoy having my livelihood attached to the consequences of their repeatedly-stupid-behaviour.
As we have seem with offshoring, any company whose main business isn't producing software, isn't coming back in-house, even if the quality for engineering team themselves sucks.
Velocity implies direction, AI is just speed sans direction, AI only workflows are just really fast brownian motion centred on training corpus mean for a task. Humans can give it direction, how good that direction is depends on human expertise.
We still need the humans, there are no cases for novel useful work I can think of, or have seen, where humans are no longer required.
Good analogy but Brownian motion is not the only type of motion in the nature. Constraints give the direction in a physical system, not humans. Evolution is the best example.
I think objections to the Theory of Evolution and some objections to the feasibility of Artificial
Intelligence have many similarities. Most people (because of their world view) assume an “intelligent” Designer is mandatory for organisms to evolve and for nature to work. They assume the nature is “random” and directionless by itself. Only a higher (supernatural) intelligence (God) can give it a “direction”. So “intelligence” is basically an external, supernatural and unexplainable (since its above our nature we don’t have access to it) phenomenon.
The exact same argument applies to AI. But instead of atoms and DNA we have bits and activations. AI is random and directionless. Only a superior intelligence (a human) can give it a direction. Like nature, a computer can’t have intelligence by itself. Intelligence is external, supernatural/supercomputational and unexplainable. You can’t compute it, you can’t understand it, you can’t replicate it.
This is because human intelligence, like God’s intelligence, lives in a supernatural realm. Some people even believe that it’s the same thing as (or a copy
of) the divine intelligence. Some others don’t believe that but still have trouble accepting their human intelligence is not a unique phenomenon and not something above this mundane world.
There, I said it. I think without this warning most of the debate and “philosophical” arguments against AI are useless. They are more like wishful thinking, shaped with the world view of the person. It’s about belief and not technical feasibility.
From the technical perspective, most of these rehired Ford folks will be replaced again in a few years. This was about overestimating the short-term effects of the automation. But in the longer term Ford will indeed have much less humans.
BTW, this new trend of “extracting the knowledge of skilled senior workers to replace them” deserves its own name. This is not a good thing for humanity, but this is exactly what they are doing.
I might not use all the same terms as you, but i largly agree. However llms live in a world almost entierly divorced from our own. Ours is physical, it's is human information corpi. For tasks suited to its world, and llm is as "human" as I am in my own domain. Same same but different. Intelligence is a fundamental trait of our universe, not a surprise.
For those of us who lived through the "Offshoring" Craze of the mid-2000s, this has the exact same arc.
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.
This is still going on, just that they try to keep a few internal tech people. The problem is the incentive for the internal people to stay as they, in theory, should not be making any changes just help out.
The solution is clearly to use an AI to communicate across cultural barriers. It can do translation too so your offshore workforce does not even need to speak your language which will cut costs even more. /s
You’ve hit on a big reason - short term gains. The partners at Accenture, Infosys and the rest circle the execs at old industry companies. The companies start performing worse, though nothing some accounting gimmicks can’t cover. Then they have a very bad quarter, enough that it will ruin their fiscal year. Fingers start pointing, and talk turns to “belt tightening” and “turning fixed costs to variable.” All of a sudden the proposals from Big Consulting that provide savings bankable this fiscal year sound very good.
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.
Which makeshype ability a API that allows the big players to comandeer small companies into suicidal behiveour , resulting in easy take overs via buy outs. So, the question is not: who is all in on the hype cycle, but who is all out.
Funny thing is, for all the commenters agreeing that this type of leadership is broken, most of the folks here and everywhere end up always doing the same things once they find themselves in similar positions of power / decision making.
Yep, because the status quo is hard to change and most people get measured, & thus, incentivized, by medium term metrics (at best). especially when investors are involved.
Because in reality, in most cases it works. I worked in many places that had large offshore teams that I worked with closely (India mostly, but also Hungary, Poland, Argentina, Morocco), and people were mostly happy with the arrangement.
There are some cases where the outcome is bad (like the case at Ford now), and lots of people point out to that and say "I told you so". But those are the exceptions, not the rule.
well yeah. the problem isn't that its easy and the execs are stupid. The problem is that its really hard, and they only have extremely fallible numbers to guide them (and the reports from various middle management layers which tend to be useless because the incentives for those guys are very far from anything that would allow ceo to make good decisions)
It's easy to see, from the outside, that a given cut stands a high chance of hurting a company. But cuts must sometimes be made regardless
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.
"Ford rehires 350 engineers after AI fails to preserve expertise or train juniors" In order to rehire someone they must laid off or fired? You don't rehire new employees?
I think most of them were losses by attrition. Where they don't replace lost employees. That's usually the preferred method of downsizing if you can get away with it.
That's just the basics. To craft a prompt for a complex architectural task, you need to know the solution at least on an abstraction level. If you don't have the right system design in your head, no llm is gonna conjure it out of thin air
> 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.
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)
Documentation driven development is your friend here. 75% of my workflow is generating documentation, at ever lower levels of abstraction, until it’s just code. The code usually comes out optimal, clean, and bug free (after passing tests) and. Suuuuuper well documented lol.
> 75% of my workflow is generating documentation, at ever lower levels of abstraction, until it’s just code
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.
I’m sure it depends on the project, stack, and dev. I know loc is a terrible metric, but …
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.
ProjectLint sounds like an excellent tool for LLMs to use! (A tiny bit is sarcasm here) but seriously, delegation of (flagging) decisions off to deterministic tools is exactly the right call whenever it’s practical to do so. We write a lot of tools for just that, often single use python scripts.
I tend to feel like, I start out with a rough idea of a program I want to write in my head. I find it easier to just write the code directly than to write a document with sufficient detail about how I want it to work for an LLM to actually write the right code, then have the LLM write the code. And the resulting documentation is about as likely to be useless or a burden as it is to be helpful in the future.
Delegation does not have to be because of a lack of knowledge. In fact, it seems like if one delegates for this reason its probably a sign of trouble to come. We delegate because of lack of time.
I guess its impossible for an executive to know ALL the details of the work they delegate, but I'd be willing to wager that executives who understand the details function better in the long run.
It certainly isn't tautological that executives be imbeciles about the businesses they run.
Maybe it’s not a binary? Maybe managers should both be able to delegate AND occasionally put in the effort to learn how things are working on the ground? Otherwise after about 3 layers of hierarchy all of the signal is gone in a massive game of telephone, leaving high level executives completely clueless.
They were conned because there’s been a massive top down propaganda campaign at the highest levels of corporate America that GAI is right around the corner.
Saying they were conned sounds like naming them victims of some trick and moving the responsibility away from them. Nah. It's not conning; it's stupidity and lack of critical thinking.
It's almost as if success in business has nothing to do with creating actual value in our society, but instead engaging in a death cult ideology of share value maximization, and that means that reasonable people are out competed in this social system by brain dead ideologues or something.
FOMO, US tech monoculture, complicit tech media hyping AI, actual religious AI believers, C-suites looking for short time gains, fear of investors‘ backlash, etc
It was a social panic. AI PR convinced tech execs that companies who didn’t adopt AI as a significant part of their workforce would fall behind (and in capitalism that means they lost market share and revenue). Investors likely put pressure on execs to do this in addition to the AI PR campaigns. FOMO is chasing the carrot you see everyone else getting, but this was more like chasing the thing that supposedly deters the stick.
It’s also worth mentioning that it still might be the right business strategy for some companies / industries. We are only 3 years into the revolution of AI for business processes and in previous revolutions there were riots, sabotage efforts, factories still being created in the style of the previous revolution, etc.
I think it’s a mix of all of this. I don’t believe one reason explains the whole mania by itself (not sure why you’re getting downvoted, your comment reads reasonable to me)
For years many in management believed our value to the company was "just" in our ability to produce code. You could see it from how they would "resource" projects and write job descriptions and manage. The output of the job, to them, was code written / bugs fixed / features implemented. In organizations like this, software was a cost centre, and it was treated that way.
LLMs can write code. They're actually pretty good at it. So problem solved, right? Cost centre cost reduction. Bam!
In reality the more competent in the job were really good at understanding business problems and holding domain specific knowledge, working with the other people on the team to translate that into a problem a computer could solve, and with understanding and diagnosing what was happening in the broader system, not just in a "program."
Someone needs to write the prompts given to the LLMs and decide if what they came back with even makes any sense. Someone needs to respond to pages in the middle of the night. Someone needs to be able to look at the system and have a bigger picture understanding of how it fits with the business' needs, etc. etc. That's a software engineer.
I honestly think not enough in middle and upper management really understand what software development actually is.
This comes across strongly any time you hear management talking about "fungibility of engineers". Everyone is a full stack everything engineer, and AI makes that even easier for them to trick themselves into believing.
If anything, I feel like AI has made domain expertise more important, not less, as the "confidently wrong" error case for agents has no one able to sanity check it. At least before AI a human would dip their toe in the water and usually realize that having no idea what they were doing, and not even being able to understand what the comments mean, was a sign that they need to go find someone more experienced to help.
> For years many in management believed our value to the company was "just" in our ability to produce code.
Yeah, this is nuts because at every company I've worked at it's assumed that engineers are thinking about things like product market fit, how a feature would be sold/ the "value" of the feature itself, how we would support the feature (not just the code, but how support would manage it), etc.
I don't think people realize how much of a hand engineers have in these conversations because we don't champion that, but we think a lot about the product as a whole. Obviously we don't spend as much time thinking about how the product will be sold as a sales person will, but we absolutely think about it, in my experience.
We think a lot about the business, like a massive amount about the system as a whole across these organizational boundaries.
I'm not convinced that they needed to be conned. That assumes that they're normally able to correctly make this type of decision without a dedicated effort to trick them. (Not saying there wasn't any dedicated effort, just that they're capable of making decisions with similarly poor judgment on their own)
my company spends millions a year on tokens and when asked about ROI the CTO just says "LoC is up! LoC isn't a good measure of productivity but it's a measure, right? right?"
lol for us it was token spend charts, then we’re told token spend is stupid so they create some aggregate metric of cost per line of code that also tells us nothing of actual customer value. It’s wild to me how at that level there’s zero repercussions
At least in my company the CFO came back after talking with other CFOs and then used Lovable to build an app. He then mentioned to his immediate team who then picked it and started running with it. It is now one of the yearly goals. The fun part is when it came time to put money where their mouth is they say the company has no funding. So more FOMO.
The goal is to deskill the labor of these workers. If there is a threat of a replacement which can bypass the cost of creating a new skilled worker, then the workers lose their bargaining power. It doesn't matter if the threat is a bluff so long as it is believed enough to give leverage.
They never use data to make decisions. I used to ask my managers for ROI analysis on new features they wanted to work on and they would stare blankly at me like I was speaking a foreign language. These people do things by "instincts" and for optics not because they've done any kind of analysis. Its easy for departments to be inefficient if your company is making billions of dollars per year. The million dollar losses go unnoticed.
Back in the nineties Ford ran a lot of ads about how quality was job one. But in the last twenty years their quality declined by a large amount at the same time other brands were getting better. I say that as a lifelong fan of Ford, quality was why I left the brand two years ago.
And yet all the time you spend performing those recalls should be annoying. Maybe you don't plan to eventually sell your car on the second hand market but if you do, a car without all the required recalls could have a lower value than one with all the recalls applied.
eh, every 6 months to a year I bring the car in to the dealer to handle the stack of pending recalls, during which I get a rental, courtesy of Ford. It's not much of a deal for me.
Few of the issues I've experienced with the car were clearly tied to quality issues: 1) Battery died a few times, but maybe that was user error 2) squirrels/rats nibbled the engine cable harness, a not-uncommon occurrence in our area. Only 3) auto-unlock on passenger side being unreliable is clearly a quality/design issue.
Honestly, I actually love the Escape. The pedal feel is very responsive in all driving modes, compared in particular to the 2020 Hybrid Rav4, which felt like driving a boat (maybe I didn't find the drive mode?), or the 2020 VW Tiguan which had a shockingly slow automatic transmission for an ostensibly "sporty" vehicle. And I'm not even a car guy. I also love its actual buttons on the dashboard, instead of the idiotic "everything on a huge touchscreen" that too many cars do nowadays.
Cars here are inspected yearly anyway or you go change winter tires for summer tires. (Because we lack the place to store them in typical houses.) So you are at the garage anyway every 6 months to 12. Then they can also do the other stuff
Actually in the latest J.D. Power initial quality ratings they took a big step up in quality. I think it was the first time in 15-20 years that they were on the list of recommended major brands.
(As a non American) I remember hearing a joke that goes something like “How do you fix a Chevrolette? Buy a Ford”, but nowadays I guess a bike is a better option
The new Tundra TTV6 had a manufacturing process defect that allowed shavings to get into the engine bearings, which causes catastrophic engine failure.
They still don't have a solution to the problem. The shavings amount/size is supposedly common among all engine manufacturing processes, but the new engine design has such tight tolerances that it's now problematic.
The same Ford whose bean counters caused them decades of reputational damage over skimping on rust protection? Seems like they haven't learned any lessons at all.
I think this may be a US thing. Fords built in Europe are pretty decent. Reliable (compared with most other makes), cheap parts and ubiquitous servicing. I've bought Fords (in the UK) for about the last 20 years and have in the main been very satisfied.
Ford has hired 350 engineers over the last 3 years which happened alongside short comings in using AI inspection tooling.
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.
Yes, it seems like many are missing the crucial aspect of the timing. The mistake was realized 3 years ago and auto design and manufacturing process lead times are long. Plus the occasion for the story was 'Ford returning to the top of the JD Power Quality Survey rankings', so that's another 6-18 months of reporting lag. That puts the original layoff mistakes being made 5 to 8 years ago.
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.
>Yes, it seems like many are missing the crucial aspect of the timing.
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.
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.
OP to me sounds more authentic and seems to have inside information.
After a quick search I found a publication actually mentioning about these tools:
Ford previously told Business Insider that it had developed two bespoke AI-enhanced scanning tools that helped validate that cars were properly assembled before rolling off the lot. The tools, called AiTriz and MAIVs, both debuted in 2024. https://autos.yahoo.com/policy-and-environment/articles/ford...
And after doing cursory research on these tools, it is clear they are rudimentary (as compared to SOTA LLMs), they were essentially smartphone mounted on stands and doing visual checks using the camera - so OP could be very right.
Calculator is a great analogy for that kind of specialized models. Way better than humans (and other things) at a specific task. Can't replace humans with it.
How can it be inside information if it's in a yahoo article? And why does OP alleging they are talking about technology A not B and you finding out they use technology A (while we all know they also use technology B as well) make OP more likely to be right? Very fallacious thinking
Nothing in the article contradicts their (IMHO accurate) claim. Three years ago boardrooms were not drinking the LLM Kool-aid yet, while ML-powered QC has been around for years. Remember Silicon Valley's hot dog vs not hot dog? That's pretty much all you need, only the hot dog is a car part.
Personally, for me that represents job security. Having a human with a high level of domain knowledge in the loop seems pretty required to get any meaningful results.
solution is to always do what it has seen in training data and how it was RL. But ai companies dont tell you that. so you have to reverse engineer its training and stick to to that.
These are no general purpose machines. They are shipping a subset mindset not general intelligence like they want us to belive .
A friend of mine prepared an arsenal of hooks and the like to address this and LLMs still disobey them at times.
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.
We didn't have to do that. It is, in fact, extremely stupid that we have done that. Computers are valuable because they are fast and deterministic. Fast but stochastic has no value.
I don't understand how that angle keeps surviving. It is in the interest of the rich and powerful to keep the vast majority of society in jobs and pay them a wage. That's what they use to consume the things that drive the economy which ultimately makes the rich richer. The narrative that the rich want to get rid of workers is as nonsensical today as it was decades ago when I heard it the first time. It doesn't make any sense.
Those employee wages for a product is a 20th century way of making money. Taking investor cash and paying it back with supplier "investments" is how "capitalism" works in today's economy. The labor market and products is just the money laundering cover story for ponzi schemes. It's way faster and more lucrative taking money from the rich in big chunks than taking it from the poor in teensy amounts. This is why everything sucks now, no one cares about the product.
Well, at least they learned from the experience, and that’s good.
The more interesting question, I think, is what proportion of businesses will choose the learn from Ford’s experience without first choosing to relive it?
Often people, and therefore also organisations, struggle to usefully learn from the experience of others without repeating the same mistakes, and experiencing the same pain.
Quite a few of the top talent has been picked up by their competitors, whatever they do they are not going to restore their team. The psychological safety has been broken and that will hamper their productivity forever.
I have spent a SOLID 3 full days 8h/day (plus long running tasks overnight) thrashing out a random idea for a Web application using purely Opus (mostly Max, sometimes ultracode version). I'm not a project manager, but I genuinely tried a full 3-tier spec out - design->specs->build details.
While it was significantly better than previous attempts, it still misses very basic things - sporadically. Eg. A clear design requirement was essentially adding clients, explained clearly and comprehensively. The ability to add clients was entirely missed in the build and iteration (there were multiple 'please check its all done' separate agent runs/checks).
I can imagine in a fully autonomous deployment, in even moderate complexity, even to this day would still occasionally mess up - badly enough to cause non-trivial business issues.
I haven't managed to really figure out what's the best way, but my latest thinking is really having boil down tasks to almost unit operations "add UI button, wire to Api call. End".
> there were multiple 'please check its all done' separate agent runs/checks
You could ask it to go through the spec point by point and then mark what is done and WHERE/WHY, then it'd point you towards exactly what might be missing.
> I haven't managed to really figure out what's the best way
For you, the best way is to break your code down into modules insofar as possible, so that you don't overrun the context window. Opus Max starts forgetting things the minute it begins compressing your conversation -- and multiple compressions can make for gaps in memory.
I find that it's also important to have another model serve as review/critique. I use Opus Max for code and 5.5 Pro for immediate code review. The latter will often pick up on things that might have been missed, and will usually provide good suggestions.
I've made it write a /status-line thing to display context tokens in the status line and also a hook to stop and ask to continue or compact whenever it reaches 250k tokens. For subscription I have also made it stop at 90% usage so Claude chat is not unusable between coding sessions. The greatest addition so far.
Hard to say exactly what went wrong from outside, but a frontier model not being able to implement a simple CRUD feature after 3x8 = 24 hours of work isn't "it can't do this". Let me hazard a guess from what you wrote.
The 3-tier spec (design → specs → build details) may be the cause rather than the cure. A big upfront spec has two failure modes the model can't help you with: it can quietly contain contradictions, and it can be ambiguous in ways the model resolves by guessing instead of asking.
"Adding clients" is a good example of the trap, even assuming your real spec was more detailed than the comment. "Client" is overloaded — a customer in the domain? An API client? A consumer of a service? And "A clear design requirement was essentially adding clients" is very imprecise: does the model add them, or build a UI so the end user can add them? I know this was just your comment and sorry to sound harsh but if the spec had sentences like that I can definitely see it going off the rails.
Your own conclusion, smaller, concrete units, is the right direction. Except by units I don't mean partitioing the program into smaller units (files, modules). In fact, you should stop thinking about implementation at all. I'm thinking more about the way of asking the LLM to build it. One feature at a time etc. so you can tighten the feedback loop. Then you can early on (in the first hour say): "I also need a way that the user can add/manage clients - basic CRUD" and that small sentence might be enough the model makes it all (UI, API, backend etc.) to enable that and put it in a proper place in the app. A big ambiguous spec defers that discovery to the worst possible moment.
> I haven't managed to really figure out what's the best way, but my latest thinking is really having boil down tasks to almost unit operations "add UI button, wire to Api call. End".
And at that point you might as well just code the thing yourself.
The dream of perpetual labor machine is something capitalists are willing to destroy the planet in order to chase their fictitious dream. Oppressors must be stopped.
There was a reason why the phrase "perpetual" was used, to invoked how unrealistic perpetual energy machines are and how futile it is for the human race to chase such dreams.
How many tens of trillions of capital have been incinerated in reducing the quality of life for workers compared to actually uplifting them?
Sure, you'll need energy inputs, you're not going to beat thermodynamics. But we're not capturing even 0.01% of available energy yet, there's a lot of room to grow.
Industrial capitalism has been fantastic for quality of life. Here I am sitting in an air-conditioned office browsing HN during a workday, instead of slaving away in the fields as a peasant farmer. I'll take more automation please.
I was wondering the other day why we didn't put this level of effort into building a highway across the Atlantic and the Pacific. It seems to me if we just piled bricks made with all the money dumped into AI in the ocean, we could easily have done this. Likewise we could have just build a canal across the United States from the Atlantic to the Pacific. These efforts would have drastically reduced shipping costs and risks but they look impossible (and stupid) on paper so no one tried them.
Why is AI different?
Because it happens in a computer and many people think that makes something easy, like CGI or computer hacking in movies. It's intangible magic and belief is the product sold to investors.
There are two kinds of knowledge. There is explicit knowledge which can be codified easily in markdown files or a wiki. Then there is tacit knowledge which is mostly encoded in the experience of an organization's individuals. Explicit knowledge is like the tip of a giant institutional knowledge iceberg.
I think that this is doable. Similar to having a new employee shadow a more experienced one and observe, you could implement a sort of program where AI shadows experienced employees and asks questions when they do something it doesn't understand.
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.
And that tacit knowledge doesn't have easily quantifiable value, it doesn't show up on the P&L so most execs don't consider it. I've seen it time and time again over my career, someone leaves or layoffs happen without considering this and then the company is scrambling to figure out processes that someone was quietly running or maintaining for years that no one else even thought of.
I have a simple mind. I think of a company with 100 employees building a dozen houses at a time. That company could replace a six-person framing crew with a two-person, one-robot team as an experiment. They could do various experiments to see if there was a better option here. It would be at the expense of four employees.
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.
I feel like "Company ditches staff in favour of AI" stories currently fit into two categories 1) The CEO is actually ditching staff for other reasons like falling revenue, but "going AI first" sounds a lot better 2) The CEO is making a mistake.
My speculation is straightforward: adding “AI” to the sticker ups the share price, dropping headcount improves the balance sheets upping the share price, and doing both at once could be perfect for a CEO bonus or strategic board member sell off.
I was diagnosed with Parkinson disease in 2018, I had tremors and severe muscle weakness, I also had stiffness and balance issues. In 2022, I was introduced to PD-5 Ayurveda treatment program from Limitless Natural Wellness (Go to Limitlessnaturalwellness .com). I read some studies and immediately started on the PD-5 protocol; I noticed changes within months. I noticed the tremors stopped and my mobility improved; the body weakness and balance/gait issues also improved significantly. After completing the treatment, I am happy to report that my Parkinson disease is well under control. I feel very good and energetic these days!
The dystopian future where no one owns cars is already being laid.
Cars are more and more becoming white goods appliances with the driving experience becoming less and less a priority. Even enthusiast cars now are about raw numbers and need electronics to reign them in to make useable for the average driver on the average road.
The average user probably doesn’t even want to drive and have AI do it for them.
Repairability is becoming less viable as mechanical parts replaced with screens and digital locks. Parts availability is already an issue, only going to get worse especially with the pace of new cars are being churned out from China.
The end will be car as a subscription. We already have it with leasing, and BMW having to pay to use your electric seats.
> The dystopian future where no one owns cars is already being laid.
Pardon me?
We're living in the dystopian present, where most everyone has a car or several. Cities are crowded with cars -- both moving and parked -- and it's awful for humans who aren't cars.
I can't wait for the moment people switch to a subscription and the cars are shared and drive themselves. The streets will be just as full of moving cars, but at least the parked cars hopefully disappear, giving us more space for trees or sidewalks or anything but cars really.
You are injecting a lot of assumptions and wishful thinking to view the removal of ownership from this equation as a net positive.
I see no reason to assume that this would lead to the disappearance of parked cars or to more trees. Our corporate overlords will want to make use of that space for more cars or infrastructure to support the new car network, why would they ever just give it back willingly?
* Their "not owning" means a swap to a subscription/license for the car, which could still be exclusive rather than shared.
* Your "not owning" assumes a reduction in the number of cars per capita.
In other words, the "dystopia" they are referring to is one that still has today's problems of gridlock, land use, urban planning, etc., with new kinds of problems layered on. Cars not being user-repairable, being nickel-and-dimed on features, a monopolistic used-parts market, and a general shift towards whatever boosts the car-manufacturer's profit margin.
This is excellent news. I'm glad some executives are starting to understand that AI will never replace an engineer with knowledge. AI is just a tool that needs guidance. If they put people without knowledge in charge of the machine gun, they will never be able to hit any target. Junior and mid-level engineers will never become super engineers by telling AI, "Just do this."
AI is a great revolutionary tool for work, but it is still a tool and needs humans to drive it. Obviously companies heard the promise of "Replace your large headcount expense with cheap tokens" and creamed their pants. Its funny to see them walk back, it will be at least a few years if not more before it replaces humans fully (and will need another breakthrough)
Back in dot-com, there used to be a website called f'ed company that chronicled the dot-com dead pool. This time around there needs to be a similar website that records AI walk backs so it helps the mgmt class not make stupid decisions.
Nice thing about the C-suite is that you get authority and compensation without responsibility. You just claim responsibility when things are good. And when bad, the underlings who have responsibilities but no authority take the heat.
This is going to happen more and more. AI is a tool that should make your employees more efficient not replace them outright. And if it doesn't make your employees better? I guess AI isn't applicable to your business then.
I can see a lot of companies coming to this realization over the coming months and years.
Exactly. Tools by definition have users. LLMs (real things) are tools. AI (science fiction) is a "person". When the "AI" demands a wage, I'll consider it real. Until then it's an LLM which is a tool. You wouldn't replace a plumber with a wrench.
I’ve had this happen a few times in the past, back when you’d fire your expensive people and replace them with cheap human labour instead of AI, so I have a word of advice.
Be sure to have “updated your rate schedule” recently, which explains why you’re now twice as expensive as before.
They know how bad they screwed up and how bad they need you now. I’ve never had anybody refuse a giant rate bump now that we were all on the same page.
Over-hiring during the bygone era of free money is now seeing an overcorrection. AI is a true if small part of it, but mainly it’s an excuse that doubles as posturing to the investor hive-mind.
Yeah, but they are short-term re-hires. Once they "get encoded" it will be bye Felica: "Ford just wants to first seasoned engineers walked out before their decades of knowledge could be encoded into automated workflows." https://www.gadgetreview.com/ford-fired-its-best-engineers-l...
(shooting from the hip)
What if the 350 engineers had built a company instead?
Union-like efforts could focus on creating new companies (having the "union" is about ensuring a certain level of organizational knowledge, like YCombinator creates a structure around startups)
I think companies would more careful about how fast and lose they operate, if firing may mean having to contract with a 3rd party.
Funny how almost every wave of automation starts the same way: "we're gonna cut headcount," but ends with "we're just shifting roles"
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
Problem with thinking you can replace your employees with AI, this is not the case. This is like thinking you could replace your NASA engineers with IBM computers in the 60s. The AI revolution changes drastically the way people work, and empower them, they multiply their productivity, but they never ever replace domain expertise, and business logic.
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.
If they gave the engineers appropriate severance packages, then they're at least out that much as a stupidity tax, but that's probably the most we can expect as far as consequences for the exec suite.
Presumably they're also out the top 10-20% of talent which immediately found jobs elsewhere and would have little interest in returning to Ford to work under such incompetent management.
Wouldn't be a bad deal tbh depending on age and how much you have already for financial independence in retirement.
If my employer offered me a deal that would allow me to retire early, comfortably, to train my AI replacement, I'd take it. If they succeed, well I'd have gotten laid off anyway. If they fail, I get to laugh all the way to the bank with my newly found free time.
This sentiment feels like a relic of a previous age. Yes _maybe_ but it's also equally likely that the best they laid off was on the ropes for months trying to battle ghost job spam and AI filters. It's almost shaming anyone who isn't hired someone immediately as deficient and "not the best". Honestly the conversation should be focused on how the execs can he made responsible.
That's fair. My intent was not to shame the "bottom 80%" which is of course most people, but rather to make a call for accountability. Like specifically the execs should have to answer to their board not just for the wasted time and severance packages, but also for the cost of losing some staff permanently with these shenanigans.
I am quite sympathetic to your position. Seeing those who manage to evade accountability consistently paying a heavy personal price was immensely satisfying. But at the same time, I don't think it resulted in any structural changes that minimise the proportion of accountability-evaders plauging society.
Ideally of course everyone, irrespective of any immutable traits they may have, gets to enjoy a healthy, satisfying, and stable life with plently of avenues for upward mobility. Short of that ideal, a society which equally burdens the rich and poor with devastating, seemingly random, unavoidable life-chaning events is decidedly better than one which only affects the poor.
So for these reasons I don't advocate for the actions of "the kid" but I don't think the consequences of his actions were in any way "bad" per se.
There is a huge cost for this either way (severance packages, yes, but also lost productivity, reduced team coherence, etc), but that unfortunately doesn’t necessarily translate to a political cost for the managers involved in pushing the dumb idea, particularly if the CEO was pressuring everyone for cost savings. They will escape by saying, “We did it because everyone else is doing it and we were told it was the right thing. How were we to know that it wouldn’t work?”
> We did it because everyone else is doing it and we were told it was the right thing. How were we to know that it wouldn’t work?”
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??"
And the board is pulling down $300k per year or more for sitting in maybe 11 meetings per year and participating in a “comp committee” where they just review data and recommendations from comp consultants and agree to whatever the consultants tell them. So, why rock the boat?
> You don't become a pioneer in your industry by just cargo culting everyone else.
You usually don't become a CEO of a long established company by being a pioneer either though...
You may be able to argue this particular case though, as he is a marketing guy and he was a pioneer in marketing as few others capitalized on social media/YouTube when he did.
But I feel like that's completely unrelated to how adjacent that's to what I'd consider a pioneer in a CEO position. Hence me pushing back a lil
Sometimes you do get the CEO gig for being a pioneer, but then the whole organization thwarts whatever you want to do by repeatedly saying “we don’t do it that way here” and dragging their feet until you get fired.
Let’s be honest about how the incentives work at large companies. The CEO probably has a $10m/yr comp package. The EVPs under him are $3m-$5m each. Nobody is really interested in making the company wildly successful, because that would entail lots of risk. Better to just keep everything moving along at the market average, don’t get fired, and collect the package every year. If you’re lucky, you do this for 3-5 years and you collect another $10-$20m termination package when they fire you. Then you hire an executive headhunter to get you the next gig and you repeat it. So, your main goal is to play defense. Don’t do anything risky that would get you fired. Pay McKinsey to bless whatever you want to do and if it blows up, blame them and call Accenture or Deloitte next time. Rotate between management consultants as required. Buy your tech from IBM, because nobody gets fired for buying IBM. Yes, your whole career will be MEH, but you can vacation all the time at your multiple houses in the Hamptons and Italy.
Why do u even bother about lost productivity. Come on dude how many firings need to happen before one has to see the reality. Just do the minimum job required for the position and move on. Loyalty should be both ways. But that's not the case
And those which return will have zero loyalty to firm.
Once you were dumped for AI gamble, you will never do the extra work, because you will probably be dumped in year or so, when someone else will get same or different stupid idea.
But it's not stupid idea, it's more like desperate attempt to remain in game in competitive market by doing what everyone else does. Idea crafted to final decision by people paid to see a bigger picture ... which unfortunatelly stop seeing smaller things which matters.
Perhaps if the rank and file at a company see personal consequence for those in the topmost posistions (salary deductions, demotions, or firing) in response to such glaring fuck ups that might even help mitigate some of these morale issues.
Absolutely. And why would you? Companies spend lots of time talking about loyalty and teamwork, but they show their colors when they do these layoffs. Smaller companies, often still run by the founder, can be much better. The only large company I ever saw command any employee loyalty was Hewlett-Packard when Bill and Dave were still running things. At one point, in the 1970s, they needed to cut payroll by 10%, so they asked the employees: we can cut 10% of the people, or everyone can take a 10% temporary pay cut. The employees voted for the pay cut. So, every other Friday, the company was shut down and everyone, all the way up to the CEO took a 10% pay cut. When times improved, they bumped everyone back up to full pay and moved on. That created huge loyalty. Unfortunately, it didn’t last. Bill and Dave passed the reins to others and eventually HP became like all the other companies and fell apart.
The social contract that American society elect (including these non executive engineers) emphasize career flexibility (right-to-work) and returns of capital than job security. Especially during booming economic years.
The frustration of being an engineer in Europe comes from the rules that this implies. Well, aside from the fact that this is mostly gone, but still exists in some big public or banking companies.
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)
That's not mandated by law though. Shouldn't companies following such stupidity be easily out-competed by those that don't? In he market for their products/services but also in the market for employment.
The kinds of companies this is talking about cannot legally be started in France. We're talking about the largest companies:
Credit Agricole, a "cooperative" bank that is ruled by union contracts that impose strict limits on how many commas in the rulebook are allowed to move per decade. A company where any change gets so stuck committees they found it easier to implement changes through parliament than through the company's own management structure. Several times.
Total, government owned oil company that gets special tax treatment and gives free shares to French presidents and ministers who leave office. Actually has a good reputation as an employer, but not because there is any chance in hell of getting promoted.
EDF, the power company (mostly nuclear), who are positively famous in how difficult they are to work with, both internally and externally. But, have a good reputation as an employer.
France Telecom, which used to be a subsidiary of EDF. They split off to remove worker protections from their (many) employees. Still extremely tied to the government. They have an extremely poor reputation as an employer (as in they have driven employees to suicide).
If you try to start any such companies in France, the government is going to outright sabotage you, whatever the laws say.
Almost nobody is covered by non compete agreements. And if you think you are, you should just ignore it anyway.
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.
> If its not symmetric then you bias towards status quo which is a really bad way to act as a CEO.
That doesn’t follow. It could just as easily bias a CEO towards over hiring, or finding ways to retrain existing employees, or any one of a million things that’s not the status quo.
It’s also possible that there currently exists pressure to push CEOs to lay off too many people and a little pressure in the opposite directions puts CEOs in a position where they are free to either layoff or hire as they see fit.
> Yeah that's not how a company should run
That should is attaching a moral judgement to this, and that’s not up to you. Many people think that the one of the primary purposes of a company is to provide employment. Even in the US our system makes it easier to hire someone than it is to fire them.
You might not want it to be a jobs program but a portion of the economy is a jobs program. I think you’re just repeating the same thing over and over so you can get the last word in.
> There’s no reason we couldn’t decide that we want to err on the side of employing too many people.
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?
> execs cargo culting on using AI as a pretext for layoffs.
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.
I assume AI lay offs are mostly investor crud anyway. I've never seen them provide any evidence or examples of where AI helped cut those jobs and it always feels like its easier to lie and say you were fired because of AI so that your fired former employees blame AI and not you. Plus, if AI is really making your org more efficient, why aren't you training your employees who are not using it effectively enough? It all smells.
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.
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).
The saying used to be "with great risk comes great reward".
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.
Layoffs aren’t “playing with people’s lives”. Employment is only by mutual consent and everyone knows that. Consent can be revoked at any time which is why anyone prudent (especially in a software engineering role) isn’t living paycheck to paycheck.
Don’t blame a customer for the vendor’s irresponsibility.
Unfortunately for this perspective, one side of the equation very much plans their lives around this mutual arrangement. When the other party experiments with the arrangement without deep consideration, I think "playing with people's lives" is very much an apt description.
Just because I would not be destitute tomorrow does not mean that my life (and those of my family) would not be deeply impacted.
> Interestingly, there were no consequences for the execs that made this 'mistake'
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 they didn’t get canned, the slap on the wrist is the cost of doing business. If we all agree to investigate ourselves and we’re all very disappointed in what happened, what a shame!
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.
> Why are you assuming this? Because Bloomberg didn’t report the execs’ performance reviews? Maybe they did face consequences and we just don’t know.
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.
That's true, but I literally mentioned the decades of experience we've all lived through, so it's not without data. When the guys who made the bad decisions are still at the company and giving interviews then that's a very strong indicator they're still there and not facing repercussions.
I imagine our current hyper-corporate landscape would have us making that assumption.
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.
Conversely, why do you jump to their defence? Large companies treat employees as a cost centre, and if a cheaper alternative becomes available then they're let go. It's not a huge leap of faith to assume so in this case.
Consequences for American car executives, are you crazy? Have you seen Stellantis cars recently? Large parts of the US (and European most likely) car industry is driving straight into irrelevance
On the topic of Stellantis, I rented one recently (through no fault of my own) and when I returned it the guy asked me how it was. I told him I wouldn't drive one of those things again if they paid me, and the guy said "yeah we get that a lot, let me get you the discount".
It sounded like they had a "Stellantis discount" for people who said something.
Jeep Wagoneer, I just remember the Stellantis logo on the infotainment boot screen. I thought it was a Stellantis Wagoneer because the Jeep logo was almost completely absent, at least in memory.
Okay so this was actually about a year or two ago, but I remember the infotainment system glitched out a lot for no discernible reason, which prevented me from accessing a lot of the controls, and I had some difficulty with the hardware controls which just felt poorly thought out from a UX standpoint.
Some of the things an owner would obviously get used to, but it felt like you were constantly struggling with it to do simple things that you don't even really notice doing in most vehicles.
The infotainment system was constantly having trouble, like freezing up or just shutting down for no apparent reason and not turning back on. I remember a lot of issues with the backup camera. Not unique for a modern car, but this one had more than its fair share of glitches. I think I had to reset it twice. It also developed an issue (sorry can't recall what it was exactly) that persisted for a day or two which spontaneously resolved itself while I was driving back to the dealership.
I want to say it had hardware AC controls (which is good), but I think I had it for three days and only figured out how to adjust it the way I wanted it on day three. I don't recall if I didn't understand that something was a button, or if a button actually had several different "modes" which weren't readily apparent, like being a combo rocker/push button. Normally these sorts of things are obvious from how the dash is deaigned, but my wife and I took three days to puzzle it out.
There were some other minor problems, but altogether it felt poorly thought out and kind of low quality, which clashed with some of the "luxury" accents my model was equipped with, like wood paneling and the lights which spelled out "WAGONEER" on the ground at night when you opened the door, which felt gimmicky. That money would have been better spent on refining the UX.
I actually don't think it was a bad drive, if you were just driving. I was just constantly frustrated trying to do anything else with it.
Thank you. Reminds me my struggle with a new cellphone about 6 or so years ago (don't remember the brand :(). Random reboots when I was using Maps (a very scary thing when you are driving in a new country), corrupted memory card and lost images, random freezing. Call quality was ok, pictures were so-so, but it is just like you said - things around main function - that's what makes or breaks the experience. On paper the phone looked really good, but the experience as whole was awful. Got back from the trip, returned phone back to Costco...
Stellantis is wild. They went from having a large portfolio of brands, each of which had many popular vehicles in America to having the Chrysler minivan, the Dodge charger, the Jeep Wrangler/Gladiator, and the Ram pickup.
I don't think it's right to categorize "no consequences".
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.
oh poor babies they got sad their human sacrifices didn't work, that's surely as much punishment as losing your livelihood because a pack of morons act randomly based on feels.
If the only consequence is that they're not rewarded, then it seems like it's very fair to categorize it as "no consequences".
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)
Generally, you don’t want to punish people for making decisions. At least I don’t. I value people who are willing to try things and I generally believe any decision made in good faith is better than no decision. My litmus test is was it a reasonable decision given the information available at the time in service of a greater goal. I can live with the consequences of that. If it turns out to be a not so great decision then we can fix it. I’m not going to fire someone for the result when the process was sound.
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.
Even from the selfish perspectives of these executives, it can be quite bad to isolate people from the consequences of bad decisions. It will prevent learning from mistakes, and lead to more bad decisions.
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.
If you're unwilling to fall on your sword and face material consequences for decisions that cause quantifiable harm the people who work for you or your customers, you do not belong in a leadership position imho, but that isn't where we are today. The people making these decisions will face no consequences for the harm they cause. Its likely they continue to be employed and receive generous compensation.
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.")
Not getting fired is not the same as isolation from consequences. People who make rational decisions and achieve results get opportunities to make more impactful decisions. People who don't get results don't get more opportunities - or maybe find themselves in a situation where the scope of their decisions (and blast radius) is limited. Firing is for misconduct or when someone has no value to offer. It's more of a spectrum than a binary thing.
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.
> People who don't get results don't get more opportunities
This shows to me that you have a lot of faith in these companies that I can't share based on my own experiences.
My experience is more like: the defining characteristics of what gets you more opportunities is personal attachment to the boss. They like you? You get more. The whole performance review culture, as an example, is based around phony justifications around this. They get to re-define what "getting results" means to favor buddies. This is the only determining factor, period, and people come across to me as absurdly foolish when they believe something else.
We only need to look at the consequences (or lack thereof) from the 2008 financial crisis to understand that there will be no consequences for the corporate class.
Society is incredibly inconsistent on this point. If a CEO shit-cans 500 people who sacrificed future career prospects for the company and end up destitute, society say's that's capitalism and they need to learn to code in a month or something. If a stay at home wife gets "bored" and divorces her husband of 20 years, he commonly owes her a decade+ of alimony to "make up for the sacrifice and time to get on her feet" or some such.
As usual it's communism for the plebs and something entirely different for the capital wielding class.
It's a good point, the counterpoint is, he really only had to cushion the post-association lifestyle of one of thousands whom became dependent on his amazon business, a tiny fraction. A typical pleb will be held to cushion the lifestyle of nearly everyone who depends on their paycheck if someone decides to terminate the relationship (usually, their spouse and kids -- in USA this doesn't extend to elderly parents though it does in some other countries).
A job doesn't usually involve a lifetime contract. And if it does, the severance required had better be incredible.
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.
I'm not sure how on earth you could consider marriage a lifetime contract when it's no-fault divorce at any second. The divorce process is at-will, though it takes some time to finalize.
While I agree that you don't want to punish people for making bad decisions, I do think there should be a carveout for when those decisions impact people's lives.
Yeah they didn’t like… migrate them to bad software they had to undo or something. They laid off hundreds of people due to overhyped products/trend chasing.
Lots of decisions impact lives. Some are literally life and death decisions. Sometimes the best decision possible with the information available at the time is going to turn out badly. Or maybe a bad decision achieves a good result.
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.
> Generally, you don’t want to punish people for making decisions.
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.
It's easy to take that stance in jest .. when it has no material impact on you. But if your life was uprooted by the decision of an executive because they made what was a "good faith" decision for the benefit of the shareholder, then I'd wager you may feel differently.
My life already was uprooted by those exact decisions... A couple times... The first guy fucked up so badly that every last one of us lost our jobs, including him. He was an unqualified moron who weaseled his way into a position where his bad decisions had major consequences. It was extremely frustrating. It happens. It will happen again. That's life.
Seems like this is a theme in our culture, maybe it's a world wide trend. The underlying theme I notice is unaccountability and selective application of rules, laws, norms to some people and not others. It seems to me like people with power, and in leadership positions like executives, get to create an environment where they are able to continually extract from a mass of people.
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.
I don't know about you, but if I was fired to be replaced by AI and then my employer came crawling, back tail between their legs, I'm pretty sure I'd start negotiations at an extra zero at the end of my salary.
That's because the company likely doesn't view it as a mistake. The executives did their job: they tried something the company likely considered reasonable (or even strategically necessary) and pivoted based on results. At the executive level, that's not considered a blunder. What counts as a blunder would be (1) being too cautious to try a change, then falling behind your competitors if that change turned out to be critical or successful; (2) attempting at change, seeing that it didn't work, and refusing to pivot or falling prey to the sunk cost fallacy.
I have mostly enjoyed AI programming and I do like using Codex. The truth is that it sometimes makes me more way more productive, but not usually. Many days are spent writing specs and babysitting prompts and it can suck. Even expensive Codex 5.4/5.5 with high thinking writes code that is just ... lazy. It takes a lot of work to get it to write excellent code. It's definitely a full time job all by itself.
I'm not talking about rocket scientist code either - I'm talking about things using raw for( instead of range-based for, or writing code that is absolutely fucking riddled with imperative logic, hacks, and kludges, when something should clearly be data-driven. Stuff that is so bad I have to tell it to start over. It routinely designs amazing architecture and absolute shit architecture, sometimes on the same day. It's just so weirdly inconsistent. If you ask it to fix a bug then you have to double check if it used a hack and sometimes it will admit to it. Sometimes it lies.
I just do not see how AI is going to replace large numbers of seasoned engineers. That would be a disaster for companies that try it. Could it replace large numbers of juniors? Yes. And maybe I am being fantastically naive. I'm 100% willing to concede that it's possible or even likely.
While being slow to pass judgment or disregard an approach is a valuable trait in a senior Eng, I think 3 years is plenty of time to wait for proof of concept to pan out. It’s not panning out, it doesn’t seem on the verge of panning out, and soon the real cost is going to be passed on and the subsidies will end. LLMs see ripe to be the new IDEs, but not the new Engineers
> Artificial intelligence is a fantastic tool, but it’s only as good as the information you use to train it
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.
The impression I'm getting over this huge number of AI roll backs is that AI is useful in some circumstances, but it's just not a cure-all. It is expensive, and increasingly so, straining the ROI scenario. My expectation is that the use-case for successful AI implementations is ultimately going to be narrow.
The world might slowly realize that a lot of generative goodness and direction is the result of our limitations and constraints as builders, not necessarily our velocity.
This doesn't seem like it backfired. Firing these people and rehiring a fraction of them catapulted Ford to the top. In fact, these roles were apparently there for over a decade before modern AI even came to exist and Ford was never top. This actually presents a formula for improved reliability - fire almost everyone, then hire back the cadre with value. A very DOGE-esque approach and I'm surprised it worked.
The best people are the least likely to come back, and going through all of that will surely impact productivity.
Just two days ago at work a call of 15+ people spent a non-trivial amount of time recounting the scars of colleagues being laid off, or they themselves having to sign severance papers, only to be saved in the final hours. These events happened 10-15 years ago and they still cost the company time a decade later, not to mention that trust that erodes with these events.
If companies want people to focus on work, those people need to feel secure in their jobs. Laying them off and hiring them back is not job security. It’s a signal that management has no idea what they’re doing. Why would these people follow the leadership of those who can’t even solve the issue of staffing without making a mess of it?
It’s also bad when seemingly competent employees are laid off while incompetent ones stick around. It sends a signal that it doesn’t matter what you do, so why try.
Well, the fact is that it seems to have improved productivity. While we can theorycraft in many ways, the reality appears to have been that firing everyone and bringing back a select few takes you to heights you could never reach for 16 years prior.
Predictably, now office workers and engineers (including here) will say "What I always knew - LLM's can't think, be creative, don't have nuance. My job is safe!". I predict the article will be quoted again and again at lunch tables and family gatherings. However, one should be especially careful when something confirms ones own biases.
Firstly, the "AI" discussed here is not LLM's. They are talking about visual quality inspection systems.
There's been many other articles in the press: Ford's new quality automation is computer-vision defect inspection, built on IBM's visual-inspection tech, iPhones photographing parts on the line, running since 2020.
By most reporting it works fine, pushing detection rates from ~70% manual to 99%+. This is classical CNN at work doing the job of quality inspectors... completely unrelated to desk-work by an engineer or what LLM's do... yet that's exactly the inference the headline invites (and many here in the comments seem to be making).
The timing only underlines it: rehiring is presented as the cleanup. Apparently the rehirings started 3 years ago, so whatever it's undoing is older still and therefore unlikely to be LLM driven. While ChatGPT did come out 3.5 years ago it seems doubtful someone would fire people left and right the moment they saw the first ChatGPT... only to then regret almost it immedaitely and rehire them - all within the span of 6 months.
This further supports that the article is about years-old automation bet being quietly unwound, and is completely unrelated to mainstream discussion about AI and jobs today.
Also, 350 rehires is just noise. Ford is shedding thousands right now: plant pauses, battery-plant retooling, projected restructuring in the 8–13k range.
Finally, as always with corporate announcements... ask why an internal staffing decision is even a press story. To me this feels like PR (a nice feel good story that ties into to a subject people discuss a lot now). It takes the sting out of all their announced layoffs. There's probably also internal company politics to it (someone suggested rehirings and now want to say 'see what a great idea this was' and maxx it out).
Problems reported in the first 90 days of ownership. Overwhelming minor niggling complaints like a piece of trim making a noise or even just misunderstandings about systems.
American automakers love crowing about that survey because it's easy to do well on. And then the car falls to shit six months later, but hey, it held together for the first 90 days so all good.
A survey is sent to car buyers with a huge number of questions related to their satisfaction. Automakers, Tier-1 suppliers, and probably others get to buy this data to mine for market research.
At a past role with a Tier-1, we bought part of the dataset. A quick regression showed that satisfaction was strongly correlated with buyer age, and there was very little signal otherwise. (Young people with overtime work and daycare pickups don't respond to surveys unless they have a serious axe to grind while retirees aren't so constrained)
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.
This seems like a totally crazy statement. The only common thing that a current and 50-year-old 911 share is that there are six holes in the engine block.
I've had two different Porsches, a Cayman S and a Macan. Neither gave me a day of trouble. You just have to do all the maintenance, which is obviously expensive.
porsche is part of volkswagen, so it's not that surprising that they're decently reliable. i probably see 10 porsches for every ferrari, lamborghini, etc that i see, and i think a large part of that is reliability - even absurdly rich people don't want to deal with an unreliable car when there is a more reliable alternative.
I wonder if Porsche is allowed to exist in point where they are not fully cost optimised so there is more spend on those slight things that keep reliability. Most other large manufacturer cars seem to be cost optimised while least amount of that is carried over to customers...
It's not like those consultants recommended something the CEO and Board didn't want to hear. They are paid to be the shield that blocks the arrows from shareholders. If they can get paid twice, once to recommend laying off 350 engineers and again to later recommend refilling 350 engineers all the better.
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.
Sorry but this reeks of marketing. To what extent was Ford actually attempting to replace these engineers with AI tools in the last three years or were they just letting them go by attrition? Was this the result of an actual AI influenced layoff? I read both the Verge and the Bloomberg piece and none of this seems to be articulated but it sure does seem to capture a vibe right now that companies are footgunning themselves all over the place with LLMs, despite no evidence of this being related to any of that...
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.
> 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.
> 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.
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?
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"
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..)
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.
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.)
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.
This was too predictable! Maybe one day AI can wholesale replace roles, but not yet. If anything, we need more seasoned people that are experienced enough to steer AI and find mistakes it makes.
Even when AI gets better, we will always need people who can troubleshoot AI itself.
> 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.
Had a couple of Taurusii back in the day. 100% ended up having a problem where the power steering pump shit the bed because a plastic piece in the pressurized side failed. Paid to repair one, oem pump broke on drive home due to same plastic piece under pressure.
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.
I had a Focus in the 2000's that was the most reliable car I ever owned. Rust got it eventually but it still started instantly at any temperature and ran like a new car.
LOL yeah I had that too. Forgot about it. Cheap fix was an aftermarket door handle from Amazon or RockAuto or someplace like that.
I'm not saying it was a perfect car. The interior was cheap, the sheet metal seemed to be recycled tin cans, and it definitely showed its age by the time I got rid of it. But that engine and drivetrain seemed to be bulletproof.
It was also designed by European engineers, not in Michigan. Not saying that's the reason the Focus is more reliable than a Taurus but they didn't follow the "typical" Ford design process at the time for that vehicle. For what it is worth I owned a 1992 Taurus and it left me stranded more times than I can count. Just some of the issues I had were a water pump that exploded and a seized A/C compressor.
Pretty much everything Ford brings to the US that was designed in Europe is loathed by anyone who has to own it out of warranty.
Turns out that when you have a building full of engineers in Germany or England their domestic engineering culture results in work output not all that different from the sort of stuff people chastise BMW and Land Rover for.
That said, the Escort, and to a lesser extent the Focus, are generally considered very good vehicles.
This idea is everywhere right now, that AI is some magic black box that will solve all your business problems. The sentiment is spreading through the exec team where I work now too. It's like a disease.
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.
> 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.
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.
I think you are misleading people by calling it a "hype cycle". There is no going back from this technology. It is going to encroach every part of lives more and more.
What does hype even mean concretely? I think this is just a coping mechanism if you ask me.
Hype cycle doesn’t imply the technology has no value. But we should be able to talk about it as the boring, nerdy technology it is without that whole doom trolling and “AI will literally solve everything”
Er, what? Intricacies of a transformer pipeline might be boring and nerdy, but the results are not. BTW, I've yet to find any strong argument on why the current ML approaches are bounded below the level you find appropriate to be bored.
The idea is there’s a rush of irrational exuberance when an “innovation trigger” makes a new toy looks promising, and everybody rushes to use it for everything, regardless of whether its suitability-for-purpose is proven. Inevitably many of those pioneers find that it’s not good for their particular problems after all; usage reaches a “peak of inflated expectations,” and crashes into a “trough of disillusionment.”
Then the tech enters a quieter and more gradual “slope of enlightenment” as people work out use cases where the tech actually adds value; then adoption reaches a “plateau of productivity.”
Worth a glance at the way they map this to prior waves of technological exuberance.
From your video, it looks like your definition of hype involves a situation where eventual adoption increases above what is in the hype today.
Here's what the parent comment thinks:
> 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.
Obviously the parent doesn't think of hype the way you think of it because they claim that big data was pointless -- they don't see the eventual "slope of enlightenment". They think of hype cycle in the colloquial way and I was responding to that.
I see this all the time in the website and frankly the patronising "but actually hype means something else" is pointless and pedantic. I urge you to respond to words within the context and not bringing in academic definitions.
The person I replied to put words in your mouth. You and I agree what you meant. You mean that the hype would die down and won’t come back up again. Ever. So reply to the person above who thinks you mean hype this way.
AI is particularly infectious among C suites, because AI is great at spewing words. A substantial portion of folks in those positions are there because of family connections, existing wealth, etc., and their only contribution to the business is similarly spewing words. They went to good colleges where they excelled at spewing words. They worked cushy / hard jobs where they had to spew the just the right normal predictable words for this context, perhaps at a large volume and with little notice... and the words were hard words... not known to those outside the industry.
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.
> 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.
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.
> 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.
And that's how you get a new war. Line must go up isn't only for the corps, its for US GOV debt too. Interest payments are already close to $1 trillion. As soon as GDP growth doesn't stay ahead of the compounding interest, the music stops. The line must go up or you get a sovereign deb crisis. When all other avenues are expended, the gov must force the economy to expand by any means necessary. Historically, that meant war.
Government debt can go down too. Democrat governments have been historically pretty good at balancing the budgets - only for their Republican successors to waste all of the effort on tax cuts for the rich and, yes, yet another dipshit war.
> 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.
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
> 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.
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.
Earlier this year I’ve been in calls with leaders from top US companies where their strategy was basically “we have to switch absolutely everything to agentic right now, otherwise we are dead”. That was the full thought.
That made reading their subsequent layoff blog posts pretty depressing
I wouldn't go back, regardless of salary offer, unless I didn't have any other jobs lined up. If I'm not employed than any job (even a bad one) beats being unemployed. But if I was employed, I wouldn't go back to a job where they laid me off for stupid reasons, no matter how much money they offered.
When you first lose everything, in the process you end up having to pawn expensive principles like that, so when other things like this happen, it's easy to seize the opportunity.
American tech is basically a sales machine. An ounce of tech will be coated with a ton of selling force. Everything in America is a business, presentation or a talk-show - including government, education, relationships. People do selling and faking to themselves sometimes.
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.
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.
It makes sense if ruining lives is good for the company, firing and layoffs that are /necessary/ are hard for anyone with empathy. They should be rewarded for doing that.
That’s very appealing, the problem is the prompts control the results to such a degree, the person composing the prompts are the executives and at that point, you have not done anything.
The value of the ai firms isn’t in building a useful tool to increase productivity of your staff by 20%. It’s not an electric drill.
It’s to replace 99% of your staff. In every industry.
Ai will be a useful tool, but either companies like OpenAI are massively overvalued or the economy will completely vanish at a high speed and their valuation will be meaningless.
Get ready for this to become a common theme. Boardrooms are still engaged in the fever-dream promise that AI will solve all their problems, particularly those involving pesky humans. The simple lesson of "AI is another tool" will be a hard-learned one. Some industries, such as software, will take more time to mop themselves into a corner before they discover that velocity should never be a first-class concern. Speed should only come as a side-effect of quality.
Nah, that’s the future executives problem, the current executive gets to brag about how their AI integrations cut costs while maintaining an acceptable yet enshittified quality
Oh, it solves two problem at once: overpaying wages and overdelivery of quality.
You just have to get the input coefficient right. The least amount of acceptable quality with the least amount of costs is the sweet spot. /s
You're being sarcastic, but...
You seem like a person who works at a place that doesn't have an AI mandate. That sounds nice. I miss when we had nice things in the world like that. I will never take that for granted again.
Why would you assume that?
The wisdom to understand that velocity is not equal to value; and the optimism that this will all end at some point.
Companies ultimately don’t have a choice here.
They can do what works, or they can fail. Large enough companies with enough inertia can do really dumb things for a while, but even giants fall.
or they just need really capable AI that are better than 99% human
If that ever happens the limiting factor will be management.
Perhaps that's where it gets interesting.
I'm confused by your answer because I can't tell which way you're going.
Are you saying companies have to mandate AI everywhere?
Or are you saying the exact opposite, as your second sentence suggests?
I haven't heard of AI mandates in small companies, only in big ones.
He's just making a general "efficient markets" argument. He's arguing that whatever happens in a couple of years will be the right thing, no matter what is happening now.
That is essentially not an argument in any direction.
Inshallah
It’s also one which ignores the “market can stay irrational longer than you can stay solvent”
If it works. Where is this 100x software output? I just see more AI tools to check it does not derail, but where is the actual software revolution, where all developers are fired? I'm still closing AI PR slop here
If it is 100x anything more interesting than line count, it will be micro-projects: Local barber wants a new website. Architecht wants to put their own plan into a numerical physics simulation library someone else wrote that has its own syntax. Schoolkid wants a customised word puzzle app for the foreign language they struggle with. They couldn't possibly code it themselves, but they can check what it is doing.
Trust without verification though, we're waiting for AI's Challenger disaster equivalent.
I'm not going to speak to the output side of your comment, but yes, developers are being fired over AI.
> The latest layoffs across all tech companies. So far in 2026, there have been 421 layoffs at tech companies with 157,807 people impacted (882 people per day). In 2025, there were 783 layoffs at tech companies w/ 245,953 people impacted (674 people per day).
https://www.trueup.io/layoffs
The fact that rich CEOs firing saying "it's because of AI" doesn't make it true. It's just marketing for investors
That just means he’s not a middle manager or exec, not that he isn’t cashing the check from someone who is clearly a short sighted idiot.
It wasn't meant to be a literal statement, more just a reflection that the situation is so bleak that I cannot imagine a better future; anybody expressing even a little bit of it seems to me like a somebody who has not been crushed into compliance through force.
Quoting the host of the recurring Quiz Broadcast sketch from That Mitchell and Webb Look: "Books mention 'hope'. What was 'hope'?"
AI mandate is one of the best things that's happened to me. It's the easiest metric to game in the world.
At one point my boss asked why my AI usage was lower than other team members. I instantly knew what to do. Every session is now run at ultracode effort. My automated PR review bot averages like $80 in usage per PR review.
It is extremely easy to burn tokens if that is required. Explore this codebase. Team x wants y feature, research and generate a full plan. What does feature x in codebase y actually mean? Analyze code coverage in x. Map out code flow and find concurrency bugs in y and on and on...
Oh and my favorite: Use 5 independent subagents to review code change and summarize the findings, and for any finding determine if they are real concerns
The other day claude spun up 100 agents and took an hour to type 30k token document to tell me something was impossible to do. I googled it, found a pr on the 3rd link that showed it was possible. "You're absolutely right!!"
"You can't use reflection if the classes aren't in the class loader" "I see why you would think that however this should work, let's test it."
-Claude, burning my company's money.
> Claude, burning my company's money.
And the planet... While I experience some schadenfreude when reading these comments from programmers, I also can not help to wonder when this insanity will this end.
There's nothing people run out of faster than other people's money. I expect this second half of the year we see that the cracks in the AI business grow and bring the whole thing down.
Just a bit after anthropic and openAI unload the "value" of their companies into retail investors.
Worse'n crypto… which I would not have believed possible.
> I also can not help to wonder when this insanity will this end.
When AI use starts to be a line item cost on public companies' financial reports + Anthropic and OpenAI have IPOed and have to file financials too + they kill their growth-hack monthly all-you-can-eat plans.
The entire house of cards falls down when the success metric shifts from "Are you using AI?" to "What return value are you getting for the money you're spending on AI?"
Some smart companies / departments are going to be able to demonstrate stellar AI ROI, but I'm going to be shocked if the bulk of current demand isn't revealed to be naked. Mostly because middle management is always stupid about adopting and using new technology.
> I also can not help to wonder when this insanity will this end.
AI companies are running out of money to subsidize those queries, and worse are needing to show a profit. All while they are having a harder time to raise more money as investment.
If nothing changes, things should become more rational soon.
... now... IMO, I place the odds of nothing changing very low...
There is value in doing all that too, though. Admittedly with strong diminishing returns, but it's there.
Eg by doing that I was able to develop non-essential features which increased our quality of life for devs last month without going through our PO who'd need to price it - because that does let's you create changes in an incredibly hands off manner with miniscule amount of time investment if you already know what you want to achieve, and how the end result should be...
Admittedly, that's a pretty narrow usecase which is rarely the case- but if it is...
And the more uselessly amusing thing is that the manager who requests higher tokens usage probably also doesn't care whether it's producing slop or not. Metric goes up; managers happy until CFO is reported income hasn't gone up as quickly as costs, and that makes the CEO optimistically concerned. Never expect underlying thought from a messenger.
It's interesting that LLM barely had any vetting period or experimentation phase. Suddenly everyone was supposed to test it in production, it seems.
Afterwards, give me 5 separate documents with 10 plans each for how to implement this. Triple check your work, make no mistakes. Then give me 3 distinct executive summaries emphasizing different areas.
Just ask it to "use a workflow" and it'll spin un dozens of agents burning your token allowance in parallel.
Let us not forget /ralph-loop “explore the codebase for bugs, write tests for each bug found but do not fix the bug, only capture its existence in testing” will ensure your agent never stops burning tokens.
I am of a particular disposition that makes it difficult for me to do lie about my work, especially if I were in a firm where people are reading my chat transcripts. As much as I want to stick it to The Man, it feels a lot better for me to just say "no" and burn through my 401k until this blows over.
I'm not too proud to admit that this whole thing scares me though. I fail to see how anything will get better.
Congrats, you have a moral compass and you sound raised by good parents. The other people in these threads bragging about burning tokens, not so much.
I’ve sadly had the same thoughts lately to cash out my 401k and say farewell to software development. I’m hanging in for a little longer, I think the AI/greed fever breaks sometime soon (months not years).
That's corporate eco-terrorism. How did we sink so low?
It's even worse/better. It's corporate financial malpractice. At some point they will wake up after the AI psychosis dies down. That might take 1-2 more years. After that most companies will realize that AI is a tool, as OP said, and adjust budgets accordingly.
Importantly, "adjusting budgets" here is for most companies, you know the ones you have to fight to even get an IDE license, a euphemism for zeroing the budget.
Hello, I am from a company whose IT leadership that saw this silliness 3 months ago.
Yes, all developer-focused AI subscriptions have been cancelled, and only AI features tacked onto existing subscriptions are part of the AI strategy (eg: Jira+AI, Confluence+AI, Analytics suite du jour+AI, Microsoft Copilot Pro (SHUDDER), etc etc etc.)
Yes, it is virtually impossible to get any additional spending approved.
Yes, there is no more Claude, there is no more Codex, it is all gone now. The AI hype occurs only in company-wide emails about commitment to modernization (with AI), reorganization (with AI), and consolidation (with AI), where no actual strategy is proposed other than what the management consultants advise (with a caveat that there is no budget for anything other than AI features that are tacked onto existing subscriptions at no additional cost.)
@ihsw you’re currently greyed out so I can’t reply, but lol holy shit i’d be updating my resume if i were you
Or maybe that's the wrong direction and this is where most of the world is headed once the true costs and ROI are fully revealed.
If your manager is asking you why you aren’t hammering 500 nails a day with your company hammer under threat of replacement, you’re going stop worrying about the surfaces your driving nails in to and simply start swinging.
1. It is not comparable. Idk the environmental toll of 500 nails, but tokenmaxxing definitely has one. Especially when it doesn't have any provable and substantial benefit.
2. Your responsibility doesn't end because your manager says so.
3. It's not just about the employee who actually burns the tokens, but also about the rest of it: the idiocy up to the top, and the irresponsibility of the companies offering the service.
> 1. It is not comparable. Idk the environmental toll of 500 nails, but tokenmaxxing definitely has one. Especially when it doesn't have any provable and substantial benefit.
Then pretend it was 5 million nails a day from a newly invented nail machine gun. This also has no provable and substantial benefit. Build a house that way and it will quickly be more nail by mass than everything else combined.
I don’t disagree. The point is capitalism operates entirely on incentive to keep our jobs or die on the streets. If they say “use all the nails or you lose your job,” people aren’t going to care about the waste or broader costs. Nails, AI, choose your example. It’s the same result unfortunately.
The point about capitalism isn't really accurate. Communism had the same problem. It's more about greed and power, and a system that sustains it than about the ideology behind it, I think. However, their ideological opposites, anarchism and liberitarianism, offer false ways out, too, as humanity is simply not capable of sustaining that.
I'm sounding a bit like a broken record, but the only political system with a proven track record in modern society is still social democracy: educate the people so they don't bash each other's heads in, distribute wealth and power better, and regulate the markets. It unfortunately died through the unholy matrimony of material well-being and social media.
The reason I’m saying capitalism is because the context is employment + the US. In the US employment is everything. It’s social status, it’s the roof over your head, it’s healthcare, it’s your identity.
Similar issues exist in communism too. It doesn’t mean you can just go “but communism” to dismiss me when I raise an accurate and valid critique of the system Ford operates in.
It wasn't meant as a riposte or anything. I just didn't read "capitalism" as "the system" but more as "the root cause" and hence what has to be changed.
In the US context, it is certainly a root cause among others.
Stock prices have always been more important than a habitable environment.
The really stupid thing is that shareholders are also rewarding useless burns of their money. It's capitalist Stakhanovism.
https://github.com/dtnewman/burn-baby-burn
Get ready for that promotion!
I love how the images are an AI-generated fever dream. Normally I hate those things, but in this case it's a perfect match for the AI clown world.
The real unlock is at line 149 of bin/burn
I'd unironically like my workplace to cover AI spend for me.
There's so, so much mechanically simple but time consuming refactoring that should be done but nobody ever does that because there's never enough free time. Or even various utility scripts and at least finding out of date docs (or writing very basic ones where none exist, though it'd be hard to get them not to feel like slop writing). Or figuring out what additional custom linter rules would be useful, how to improve the CI pipelines and so on.
If I had the Anthropic Max 20x subscription, I could make a large part of the technical backlog disappear (relatively safely).
> If I had the Anthropic Max 20x subscription
Most of the tasks you have listed you could do with Haiku, GPT mini, or DeepSeek Flash.
An Anthropic Max 20x subscription is considerable overkill for this sort of task.
I've had great success with OpenCode Go and DeepSeek v4 Flash for Terraform code refactorings and extensions. It's cheap enough to pay it yourself ($5 first month, $10 afterwards). Ideally you provide the model a feedback loop (e. g. passing tests) so it can safely iterate.
There will always be more work to do, especially for someone else's company.
What's the rush? Friday will still come at the same speed, and it's unlikely you will receive an increase in pay to account for your increase in productivity.
It's also the easiest way to determine if your management has AI psychosis or not, and make corresponding decisions about whether to stay with the company.
No one is leaving their job because their manager is too obsessed with AI. Especially not in this economy/job market.
Parkinson's Law: Work expands to fill the time available.
Updated version: Tokens expand to exceed the budget available.
Fantasy: automated productivity
Reality: automated bullshit makework and bureaucracy
Get out of thay world ASAP. There are still companies actually doing work instead of burning investors money
as a CTO, its been crazy pushing back against these AI mandates. Almost always from VCs and non technical contributors. I'm pretty liberal about using AI but it has its limits. I think of them like swim fins. you can dive much deeper with them but if you didn't earn that ability, you can find yourself too deep to get your next breath of air. likewise, its important to never let the ai do work more than one ring outside of your knowledge base lest it do things you dont' understand and therefore can't audit.
It's not unreasonable to mandate that one should try it for some of its safer uses, or to spend time teaching people what the good uses are, which keep growing... but mandating a significant part of the day-to-day is telling employees they have no agency in how they achieve objectives. For people that aren't technical, it shows they aren't good at the social either.
The company I work for, thankfully, is a bit like that.
The AI initiative there is a lot more in "let's try to find ways that this can be useful" instead of "let's use this to the maximum extent".
So far it has been a mostly positive experience. We could figure out ways where it saves time instead of burning money in a token pit.
The only downside is that code reviews are becoming the bottleneck. Every PR still needs a human reviewer, and that is not changing. The influx of PRs increased slightly, the rate of reviews not as much.
Our AI mandate is coming. I'm trying hard to be a voice of reason, but it's bows and arrows against the lightning, I'm afraid.
To the boardroom class, employees are tools as well.
No doubt, but the issue I think they keep running into is they don't understand how useful those "human tools" are, so they keep trying to replace the functions humans provide with AI, without realizing all the other functions that the humans also provided.
Marx had a way to think about that. He would distinguish between labour as in generalized socially necessafy labour, and specific skilled labour.
Value is measure in generalized labour, since that the universal measure of human effort. The genealized amount of time a human being must spend to produce something from its parts. Generalized labour is also what's bought from labourers. You don't pay them to do something specific, you pay them to labour in general.
This contrasts against specific labour, which is whats actually required in the moment. Generalized labour power must be the right kind of specific labour to actually produce anything of value.
The AI leaders have been told that AI is labour. To the extent that it currently is, which I believe is only the case because the market hasn't adjusted, it's not the right specific labour to male anything valuable.
I find this comment, on it's face, very hard to understand. An apparent abundance of qualifiers without definition. Is this an example of circular reasoning?
It seems to me that the text is saying that generalised labour produces value, but then only specific labour produces actual value. What is the difference between actual value and value in general? Is some value somehow more valuable that other? Are we even speaking the same language? Is this just making shit up as you go along and hope nobody notices because the general idea is appealing?
My partner had booked a table for lunch for us and our friends. Six adults and six children. One of the couples had forgotten a party earlier that morning, so we tried to move the booking a couple of hours later.
Unfortunately the only phone line was answered by an AI bot who stubbornly refused to move the booking, simply telling us there was no availability within an hour of our booking.
Fortunately my partner was passing so was able to go in and speak to someone is person who was happy to move our booking back 2 hours. Lunch and drinks for our party must have come to several hundred pounds.
I'd estimate our party was between a third or maybe half of all the customers there. Had we chosen to book elsewhere I bet someone would still be patting themselves on the back about how clever they were to save a few minutes a day on actually answering the phone to actual customers.
It's the conceit of capitalism. We've structured our entire society around giving the boardroom class most of the rewards from our societal output, so they've taken that to mean they create most of the value. They are job creators, deliverers of technology, builders of nations, and how it gets done at the low level is an fungible implementation detail. Whether it's slaves or workers or robots down in the fields / mines / factories, the board are the ones driving the ship and therefore doing the real, important work.
And yes, this does mean they view us workers as somewhere between slaves and robots, replicable by a token predictor.
I wish I could work somewhere where I’m _marginally_ less subject to the whims of the Boardroom class.
I’m sure they’re having a great time, and getting filthy rich doing it, but I don’t enjoy having my livelihood attached to the consequences of their repeatedly-stupid-behaviour.
As we have seem with offshoring, any company whose main business isn't producing software, isn't coming back in-house, even if the quality for engineering team themselves sucks.
Velocity implies direction, AI is just speed sans direction, AI only workflows are just really fast brownian motion centred on training corpus mean for a task. Humans can give it direction, how good that direction is depends on human expertise.
We still need the humans, there are no cases for novel useful work I can think of, or have seen, where humans are no longer required.
I like the analogy with brownian motion, thanks for sharing that
Good analogy but Brownian motion is not the only type of motion in the nature. Constraints give the direction in a physical system, not humans. Evolution is the best example.
I think objections to the Theory of Evolution and some objections to the feasibility of Artificial Intelligence have many similarities. Most people (because of their world view) assume an “intelligent” Designer is mandatory for organisms to evolve and for nature to work. They assume the nature is “random” and directionless by itself. Only a higher (supernatural) intelligence (God) can give it a “direction”. So “intelligence” is basically an external, supernatural and unexplainable (since its above our nature we don’t have access to it) phenomenon.
The exact same argument applies to AI. But instead of atoms and DNA we have bits and activations. AI is random and directionless. Only a superior intelligence (a human) can give it a direction. Like nature, a computer can’t have intelligence by itself. Intelligence is external, supernatural/supercomputational and unexplainable. You can’t compute it, you can’t understand it, you can’t replicate it.
This is because human intelligence, like God’s intelligence, lives in a supernatural realm. Some people even believe that it’s the same thing as (or a copy of) the divine intelligence. Some others don’t believe that but still have trouble accepting their human intelligence is not a unique phenomenon and not something above this mundane world.
There, I said it. I think without this warning most of the debate and “philosophical” arguments against AI are useless. They are more like wishful thinking, shaped with the world view of the person. It’s about belief and not technical feasibility.
From the technical perspective, most of these rehired Ford folks will be replaced again in a few years. This was about overestimating the short-term effects of the automation. But in the longer term Ford will indeed have much less humans.
BTW, this new trend of “extracting the knowledge of skilled senior workers to replace them” deserves its own name. This is not a good thing for humanity, but this is exactly what they are doing.
I might not use all the same terms as you, but i largly agree. However llms live in a world almost entierly divorced from our own. Ours is physical, it's is human information corpi. For tasks suited to its world, and llm is as "human" as I am in my own domain. Same same but different. Intelligence is a fundamental trait of our universe, not a surprise.
> velocity should never be a first-class concern
Some people have not learned that velocity at small scale without global synchronisation is just thermal agitation.
Someone should tell this to Bungie’s Justin Truman
The word "lesson" implies that there'll be some learning involved in the process. I got your joke, right?
who would have thought :)
> Speed should only come as a side-effect of quality.
"Slow is smooth, smooth is fast."
- US Navy SEALs
For those of us who lived through the "Offshoring" Craze of the mid-2000s, this has the exact same arc.
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.
This is still going on, just that they try to keep a few internal tech people. The problem is the incentive for the internal people to stay as they, in theory, should not be making any changes just help out.
The solution is clearly to use an AI to communicate across cultural barriers. It can do translation too so your offshore workforce does not even need to speak your language which will cut costs even more. /s
This is being pushed to us in forms of AI SDLC.
I am quite heartbroken. Your /s comment is a reality for others.
Wow! I think this a relative of Poe's law in action - there is no idea you can think is satirical that someone does not think is a good idea.
You’ve hit on a big reason - short term gains. The partners at Accenture, Infosys and the rest circle the execs at old industry companies. The companies start performing worse, though nothing some accounting gimmicks can’t cover. Then they have a very bad quarter, enough that it will ruin their fiscal year. Fingers start pointing, and talk turns to “belt tightening” and “turning fixed costs to variable.” All of a sudden the proposals from Big Consulting that provide savings bankable this fiscal year sound very good.
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.
Which makeshype ability a API that allows the big players to comandeer small companies into suicidal behiveour , resulting in easy take overs via buy outs. So, the question is not: who is all in on the hype cycle, but who is all out.
I’m not sure I follow.
Funny thing is, for all the commenters agreeing that this type of leadership is broken, most of the folks here and everywhere end up always doing the same things once they find themselves in similar positions of power / decision making.
Yep, because the status quo is hard to change and most people get measured, & thus, incentivized, by medium term metrics (at best). especially when investors are involved.
> especially when investors are involved
presumably this/these are the Moloch the other poster alluded to
In many situations you realize that certain behavior is bad yet you are forced into it by game theory. It’s just Moloch’s invisible hand ruining it.
Because in reality, in most cases it works. I worked in many places that had large offshore teams that I worked with closely (India mostly, but also Hungary, Poland, Argentina, Morocco), and people were mostly happy with the arrangement.
There are some cases where the outcome is bad (like the case at Ford now), and lots of people point out to that and say "I told you so". But those are the exceptions, not the rule.
well yeah. the problem isn't that its easy and the execs are stupid. The problem is that its really hard, and they only have extremely fallible numbers to guide them (and the reports from various middle management layers which tend to be useless because the incentives for those guys are very far from anything that would allow ceo to make good decisions)
It's easy to see, from the outside, that a given cut stands a high chance of hurting a company. But cuts must sometimes be made regardless
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.
Who says Ford fired any employees? The article doesn't.
"Ford rehires 350 engineers after AI fails to preserve expertise or train juniors" In order to rehire someone they must laid off or fired? You don't rehire new employees?
Farther down it clarifies that only some of them were former employees, and others were poached from other companies:
>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.
> many of them former employees
> And not all former employees were laid off.
Thanks for confirming that the article does say that Ford did, indeed, fire and rehire some employees.
The article does not say that any of the former employees had been fired.
You just want to believe in the narrative that companies who lay people off for AI will regret it. Narratives are dumb.
I genuinely don't care about any of this.
I'm just reading what's written:
> And not all former employees were laid off.
To me, this is very clearly saying that SOME were former employees that were laid off, just not ALL were.
That's just you misreading the comment. That quote is not from the article.
I think most of them were losses by attrition. Where they don't replace lost employees. That's usually the preferred method of downsizing if you can get away with it.
What is the point of a comment like this?
This article may not mention anything but it doesn't exist in a vacuum. Go search "Ford Layoffs 2025" and see for your self
It's not up for debate whether they did or didn't lay people off recently. They unambiguously did.
What is the point of a comment like this?
Deflection.
brand bots be active on HN as they are anywhere else
That's just the basics. To craft a prompt for a complex architectural task, you need to know the solution at least on an abstraction level. If you don't have the right system design in your head, no llm is gonna conjure it out of thin air
> 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.
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)
Documentation driven development is your friend here. 75% of my workflow is generating documentation, at ever lower levels of abstraction, until it’s just code. The code usually comes out optimal, clean, and bug free (after passing tests) and. Suuuuuper well documented lol.
It’s human in the loop over and over again tho
> 75% of my workflow is generating documentation, at ever lower levels of abstraction, until it’s just code
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.
I’m sure it depends on the project, stack, and dev. I know loc is a terrible metric, but …
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.
ProjectLint sounds like an excellent tool for LLMs to use! (A tiny bit is sarcasm here) but seriously, delegation of (flagging) decisions off to deterministic tools is exactly the right call whenever it’s practical to do so. We write a lot of tools for just that, often single use python scripts.
I tend to feel like, I start out with a rough idea of a program I want to write in my head. I find it easier to just write the code directly than to write a document with sufficient detail about how I want it to work for an LLM to actually write the right code, then have the LLM write the code. And the resulting documentation is about as likely to be useless or a burden as it is to be helpful in the future.
You don’t write the doc. You talk to the LLM about the idea and the anchor points, and have it write the doc.
Just remember Visual Inspection Before Execution…
Nah, it’s only industrial process control… YOLO!
depending on who you ask, the failure is not one of AI. It's a failure of management to adopt enough AI.
https://archive.is/DI4Cq
And the verge is covering it too:
https://www.theverge.com/transportation/956316/ford-quality-...
It’s so odd to me how companies decided what LLMs are capable of without data backing it up. Were all the execs conned or something ?
These execs suffer from over confidence in their own abilities.
Thats partly why they get so far.
Most executives are complete imbeciles when it comes to the actual work their organizations do.
That sounds obvious, but here's the thing: that's what a tautologically good manager does.
They delegate and hire subordinates to do a job. It is by design that the communication won't involve 100% of the work done
You hire people to do a job, not to be a remote controlled puppet
Delegation does not have to be because of a lack of knowledge. In fact, it seems like if one delegates for this reason its probably a sign of trouble to come. We delegate because of lack of time.
I guess its impossible for an executive to know ALL the details of the work they delegate, but I'd be willing to wager that executives who understand the details function better in the long run.
It certainly isn't tautological that executives be imbeciles about the businesses they run.
Maybe it’s not a binary? Maybe managers should both be able to delegate AND occasionally put in the effort to learn how things are working on the ground? Otherwise after about 3 layers of hierarchy all of the signal is gone in a massive game of telephone, leaving high level executives completely clueless.
Yes, sure, good managers will want to know (some of that)
But that want is limited (needs to be), and also it depends on the IC to explain things
Sounds like laziness to me
It could also be that business conditions provided a convenient opportunity to run some experiments.
They were conned because there’s been a massive top down propaganda campaign at the highest levels of corporate America that GAI is right around the corner.
Saying they were conned sounds like naming them victims of some trick and moving the responsibility away from them. Nah. It's not conning; it's stupidity and lack of critical thinking.
Fair point!
It's almost as if success in business has nothing to do with creating actual value in our society, but instead engaging in a death cult ideology of share value maximization, and that means that reasonable people are out competed in this social system by brain dead ideologues or something.
Can’t tell if you’re being sarcastic or not, but yes, actual value is at best tangential to success in business.
Things have moved from "no one got fired for buying IBM" to "no one got fired for buying AI".
To: everyone but leadership got fired for buying AI
FOMO, US tech monoculture, complicit tech media hyping AI, actual religious AI believers, C-suites looking for short time gains, fear of investors‘ backlash, etc
It was a social panic. AI PR convinced tech execs that companies who didn’t adopt AI as a significant part of their workforce would fall behind (and in capitalism that means they lost market share and revenue). Investors likely put pressure on execs to do this in addition to the AI PR campaigns. FOMO is chasing the carrot you see everyone else getting, but this was more like chasing the thing that supposedly deters the stick.
It’s also worth mentioning that it still might be the right business strategy for some companies / industries. We are only 3 years into the revolution of AI for business processes and in previous revolutions there were riots, sabotage efforts, factories still being created in the style of the previous revolution, etc.
I think it’s a mix of all of this. I don’t believe one reason explains the whole mania by itself (not sure why you’re getting downvoted, your comment reads reasonable to me)
"everyone! emergency! we need AI yesterday! we're going to do a company wide hackathon!"
"everyone! ship ship ship! make production ready versions of what was triaged from the hackathon! nnnowwwwww"
"everyone! wow 80% correct, prompt engineer it to be stricter.... and with a bigger model! wow 98% correct! this whole division is made redundant!"
"everyone! its not 98% accurate and even if it was, thats a huge set of errors given our volume!"
"everyone! our AI bills have skyrocketed! they're charging us differently because we're an enterprise! kill the AI, kill the AI"
For years many in management believed our value to the company was "just" in our ability to produce code. You could see it from how they would "resource" projects and write job descriptions and manage. The output of the job, to them, was code written / bugs fixed / features implemented. In organizations like this, software was a cost centre, and it was treated that way.
LLMs can write code. They're actually pretty good at it. So problem solved, right? Cost centre cost reduction. Bam!
In reality the more competent in the job were really good at understanding business problems and holding domain specific knowledge, working with the other people on the team to translate that into a problem a computer could solve, and with understanding and diagnosing what was happening in the broader system, not just in a "program."
Someone needs to write the prompts given to the LLMs and decide if what they came back with even makes any sense. Someone needs to respond to pages in the middle of the night. Someone needs to be able to look at the system and have a bigger picture understanding of how it fits with the business' needs, etc. etc. That's a software engineer.
I honestly think not enough in middle and upper management really understand what software development actually is.
This comes across strongly any time you hear management talking about "fungibility of engineers". Everyone is a full stack everything engineer, and AI makes that even easier for them to trick themselves into believing.
If anything, I feel like AI has made domain expertise more important, not less, as the "confidently wrong" error case for agents has no one able to sanity check it. At least before AI a human would dip their toe in the water and usually realize that having no idea what they were doing, and not even being able to understand what the comments mean, was a sign that they need to go find someone more experienced to help.
> For years many in management believed our value to the company was "just" in our ability to produce code.
Yeah, this is nuts because at every company I've worked at it's assumed that engineers are thinking about things like product market fit, how a feature would be sold/ the "value" of the feature itself, how we would support the feature (not just the code, but how support would manage it), etc.
I don't think people realize how much of a hand engineers have in these conversations because we don't champion that, but we think a lot about the product as a whole. Obviously we don't spend as much time thinking about how the product will be sold as a sales person will, but we absolutely think about it, in my experience.
We think a lot about the business, like a massive amount about the system as a whole across these organizational boundaries.
I'm not convinced that they needed to be conned. That assumes that they're normally able to correctly make this type of decision without a dedicated effort to trick them. (Not saying there wasn't any dedicated effort, just that they're capable of making decisions with similarly poor judgment on their own)
there is no measurement of ROI
my company spends millions a year on tokens and when asked about ROI the CTO just says "LoC is up! LoC isn't a good measure of productivity but it's a measure, right? right?"
lol for us it was token spend charts, then we’re told token spend is stupid so they create some aggregate metric of cost per line of code that also tells us nothing of actual customer value. It’s wild to me how at that level there’s zero repercussions
Fully red pilled, I literally cannot believe the rhetoric I’ve been hearing inside major companies.
At least in my company the CFO came back after talking with other CFOs and then used Lovable to build an app. He then mentioned to his immediate team who then picked it and started running with it. It is now one of the yearly goals. The fun part is when it came time to put money where their mouth is they say the company has no funding. So more FOMO.
The goal is to deskill the labor of these workers. If there is a threat of a replacement which can bypass the cost of creating a new skilled worker, then the workers lose their bargaining power. It doesn't matter if the threat is a bluff so long as it is believed enough to give leverage.
They never use data to make decisions. I used to ask my managers for ROI analysis on new features they wanted to work on and they would stare blankly at me like I was speaking a foreign language. These people do things by "instincts" and for optics not because they've done any kind of analysis. Its easy for departments to be inefficient if your company is making billions of dollars per year. The million dollar losses go unnoticed.
I believe many have very good instincts, but they are about "do I get into trouble if I do that / don't do that"
Back in the nineties Ford ran a lot of ads about how quality was job one. But in the last twenty years their quality declined by a large amount at the same time other brands were getting better. I say that as a lifelong fan of Ford, quality was why I left the brand two years ago.
It's impressive all the recall notices I get on my 2020 Escape Hybrid. At this point I joke with my friends that they're love-letters from Ford.
(most of them are for fairly innocuous stuff...)
And yet all the time you spend performing those recalls should be annoying. Maybe you don't plan to eventually sell your car on the second hand market but if you do, a car without all the required recalls could have a lower value than one with all the recalls applied.
eh, every 6 months to a year I bring the car in to the dealer to handle the stack of pending recalls, during which I get a rental, courtesy of Ford. It's not much of a deal for me.
Few of the issues I've experienced with the car were clearly tied to quality issues: 1) Battery died a few times, but maybe that was user error 2) squirrels/rats nibbled the engine cable harness, a not-uncommon occurrence in our area. Only 3) auto-unlock on passenger side being unreliable is clearly a quality/design issue.
Honestly, I actually love the Escape. The pedal feel is very responsive in all driving modes, compared in particular to the 2020 Hybrid Rav4, which felt like driving a boat (maybe I didn't find the drive mode?), or the 2020 VW Tiguan which had a shockingly slow automatic transmission for an ostensibly "sporty" vehicle. And I'm not even a car guy. I also love its actual buttons on the dashboard, instead of the idiotic "everything on a huge touchscreen" that too many cars do nowadays.
> every 6 months to a year I bring the car in to the dealer to handle the stack of pending recalls
The fact that you find this acceptable is amazing to me.
Sounds like a complete failure of quality control.
Cars here are inspected yearly anyway or you go change winter tires for summer tires. (Because we lack the place to store them in typical houses.) So you are at the garage anyway every 6 months to 12. Then they can also do the other stuff
Still enjoying my 05 Focus, in which I have done zero recalls, although I did have to fix the persistent trunk leaks with bathroom sealant.
If a company is saying “X is job one” it’s because they suck at X. They sucked at quality. They still suck at quality.
Actually in the latest J.D. Power initial quality ratings they took a big step up in quality. I think it was the first time in 15-20 years that they were on the list of recommended major brands.
https://archive.is/VcL8c
JD power is pay to play. Ford just kicked in more money this year.
I'm very skeptical of the initial quality studies. No idea how well predict long term (or even 5 year) quality.
(As a non American) I remember hearing a joke that goes something like “How do you fix a Chevrolette? Buy a Ford”, but nowadays I guess a bike is a better option
Or more realistically a Toyota, and their numbers are reflecting this.
Which numbers are those? Their sales numbers or their numbers of vehicle recalls due to defective engine manufacturing?
They destroyed their heavier truck reputation with this new Tundra unfortunately
what's wrong with it?
The new Tundra TTV6 had a manufacturing process defect that allowed shavings to get into the engine bearings, which causes catastrophic engine failure.
They still don't have a solution to the problem. The shavings amount/size is supposedly common among all engine manufacturing processes, but the new engine design has such tight tolerances that it's now problematic.
Appreciate my 2UZ-FE more every year.
Fix Or Repair Daily
Found On Road Dead
Faulty Obsolete Ruinous Decline
There is also the ‘joke’ - What does Ford stand for? Fix Or Repair Daily.
None of the US automakers have good quality reputations. If you want something that works reliably, get a Toyota.
Ebbs and flows with these companies. If you got used to driving in the 70s then the FORD meme was “Fix Or Repair Daily”.
The other classic one is, “What’s Ford backwards? Driver Returns On Foot.”
Fix or replace daily. Fixing and repairing are the same. ;)
The same Ford whose bean counters caused them decades of reputational damage over skimping on rust protection? Seems like they haven't learned any lessons at all.
Really? Ford’s quality in the last half of the 1990s was the poster child of cheap, vac-form plastics.
I think this may be a US thing. Fords built in Europe are pretty decent. Reliable (compared with most other makes), cheap parts and ubiquitous servicing. I've bought Fords (in the UK) for about the last 20 years and have in the main been very satisfied.
Putting timing belts in oil was quite a bad idea from them though.
Ouch, did not expect to get triggered by this on HN
- Peugeot 2008 owner but not much longer
That's fair. Got stung by that a couple of years ago. Fortunately there are plenty of models without that.
Fords have a really bad name in Australia. The cheapest Hyundai will outlast even a high end Ford.
But in terms of reliability, here Toyota is king
Ford is not as protected from competition in Europe.
US software engineers need a union.
If I hadn't already landed a job somewhere else, I would only return with a 20% pay bump and an iron-clad contract.
This should be way higher.
This is a boom and bust industry. Projects come and go and only to a lesser extent if you work at a software company.
I would recommend IT/server administration as that is a constant business need, if you prefer stability with more limited upside.
Unions add another layer of bureaucracy to make small changes. This is the exact opposite of how software and technology works.
"We didn’t pay as much attention as we should have to the experience of our most knowledgeable engineers"
The defining motto of the corporate world
Change engineers to employees and you’re spot on.
Ford has hired 350 engineers over the last 3 years which happened alongside short comings in using AI inspection tooling.
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.
Yeah, it looks like this wasn't AI related. I hope yours grows to be the top comment!
Yes, it seems like many are missing the crucial aspect of the timing. The mistake was realized 3 years ago and auto design and manufacturing process lead times are long. Plus the occasion for the story was 'Ford returning to the top of the JD Power Quality Survey rankings', so that's another 6-18 months of reporting lag. That puts the original layoff mistakes being made 5 to 8 years ago.
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.
>Yes, it seems like many are missing the crucial aspect of the timing.
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.
Submitted title was "Ford rehires 350 engineers after AI fails to preserve expertise or train juniors", which is not what the article says.
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.
The article has named sources for its quotes, whereas your comment relies entirely on "almost certainly" which sounds a lot less informed.
OP to me sounds more authentic and seems to have inside information.
After a quick search I found a publication actually mentioning about these tools:
Ford previously told Business Insider that it had developed two bespoke AI-enhanced scanning tools that helped validate that cars were properly assembled before rolling off the lot. The tools, called AiTriz and MAIVs, both debuted in 2024. https://autos.yahoo.com/policy-and-environment/articles/ford...
And after doing cursory research on these tools, it is clear they are rudimentary (as compared to SOTA LLMs), they were essentially smartphone mounted on stands and doing visual checks using the camera - so OP could be very right.
https://www.businessinsider.com/ford-uses-ai-cameras-in-fact...
A fine-tuned classifier purpose fit for a specific task can easily outperform a SOTA LLM on more modest hardware and often makes a lot more sense.
If your data is sufficiently noisy or your relationship sufficiently simple a linear regression will outperform a SOTA LLM.
Calculator is a great analogy for that kind of specialized models. Way better than humans (and other things) at a specific task. Can't replace humans with it.
LLMs are not calculators.
How can it be inside information if it's in a yahoo article? And why does OP alleging they are talking about technology A not B and you finding out they use technology A (while we all know they also use technology B as well) make OP more likely to be right? Very fallacious thinking
Nothing in the article contradicts their (IMHO accurate) claim. Three years ago boardrooms were not drinking the LLM Kool-aid yet, while ML-powered QC has been around for years. Remember Silicon Valley's hot dog vs not hot dog? That's pretty much all you need, only the hot dog is a car part.
Apparently it is not all you need, according to the article.
> This has nothing to do with LLMs and instead is almost certainly about their MAIVIS and AiTriz pilots
Where does this article say otherwise?
The dirt bag media! Making insinuation that I actually projected onto their article!
You said that you misinterpreted the article in the same way in another comment 1 minute before you left this one. https://news.ycombinator.com/item?id=48705638
If you could read you'd know what I wrote there was nothing like what you're claiming
The reason AI fails in Industry is that SKILL.md or other knowledge-injection methods do not guarantee compliance. AI just thinks it "knows better".
A friend of mine prepared an arsenal of hooks and the like to address this and LLMs still disobey them at times.
I don't have high hopes that there exists a bulletproof solution to this.
Personally, for me that represents job security. Having a human with a high level of domain knowledge in the loop seems pretty required to get any meaningful results.
solution is to always do what it has seen in training data and how it was RL. But ai companies dont tell you that. so you have to reverse engineer its training and stick to to that.
These are no general purpose machines. They are shipping a subset mindset not general intelligence like they want us to belive .
A friend of mine prepared an arsenal of hooks and the like to address this and LLMs still disobey them at times.
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.
Someone is unlikely to relay a story where someone was asked not to do something and they didn't. There is no story there.
Not sure if this was ironic. I guess it mainly fails because a lot of knowledge and experience is intuitive and not codified.
If compliance was the main issue we wouldn't have had to invent ways for computers to do something other than exactly what they were asked.
We didn't have to do that. It is, in fact, extremely stupid that we have done that. Computers are valuable because they are fast and deterministic. Fast but stochastic has no value.
> Fast but stochastic has no value.
He valuations of a bunch of AI unicorns disagree.
Its all about a longshot gamble to replace workers and wages.
I don't understand how that angle keeps surviving. It is in the interest of the rich and powerful to keep the vast majority of society in jobs and pay them a wage. That's what they use to consume the things that drive the economy which ultimately makes the rich richer. The narrative that the rich want to get rid of workers is as nonsensical today as it was decades ago when I heard it the first time. It doesn't make any sense.
Those employee wages for a product is a 20th century way of making money. Taking investor cash and paying it back with supplier "investments" is how "capitalism" works in today's economy. The labor market and products is just the money laundering cover story for ponzi schemes. It's way faster and more lucrative taking money from the rich in big chunks than taking it from the poor in teensy amounts. This is why everything sucks now, no one cares about the product.
What about slow and stochastic? 9 out of 10 managers seems to agree about this, at least it seems to be that, judging through their actions.
Well, at least they learned from the experience, and that’s good.
The more interesting question, I think, is what proportion of businesses will choose the learn from Ford’s experience without first choosing to relive it?
Often people, and therefore also organisations, struggle to usefully learn from the experience of others without repeating the same mistakes, and experiencing the same pain.
I hope they demanded salary of 2x or more to return
I was thinking the same. Sadly they don’t have the leverage to pull that but hope Im wrong.
Quite a few of the top talent has been picked up by their competitors, whatever they do they are not going to restore their team. The psychological safety has been broken and that will hamper their productivity forever.
I have spent a SOLID 3 full days 8h/day (plus long running tasks overnight) thrashing out a random idea for a Web application using purely Opus (mostly Max, sometimes ultracode version). I'm not a project manager, but I genuinely tried a full 3-tier spec out - design->specs->build details.
While it was significantly better than previous attempts, it still misses very basic things - sporadically. Eg. A clear design requirement was essentially adding clients, explained clearly and comprehensively. The ability to add clients was entirely missed in the build and iteration (there were multiple 'please check its all done' separate agent runs/checks).
I can imagine in a fully autonomous deployment, in even moderate complexity, even to this day would still occasionally mess up - badly enough to cause non-trivial business issues.
I haven't managed to really figure out what's the best way, but my latest thinking is really having boil down tasks to almost unit operations "add UI button, wire to Api call. End".
> there were multiple 'please check its all done' separate agent runs/checks
You could ask it to go through the spec point by point and then mark what is done and WHERE/WHY, then it'd point you towards exactly what might be missing.
> I haven't managed to really figure out what's the best way
For you, the best way is to break your code down into modules insofar as possible, so that you don't overrun the context window. Opus Max starts forgetting things the minute it begins compressing your conversation -- and multiple compressions can make for gaps in memory.
I find that it's also important to have another model serve as review/critique. I use Opus Max for code and 5.5 Pro for immediate code review. The latter will often pick up on things that might have been missed, and will usually provide good suggestions.
I've made it write a /status-line thing to display context tokens in the status line and also a hook to stop and ask to continue or compact whenever it reaches 250k tokens. For subscription I have also made it stop at 90% usage so Claude chat is not unusable between coding sessions. The greatest addition so far.
Hard to say exactly what went wrong from outside, but a frontier model not being able to implement a simple CRUD feature after 3x8 = 24 hours of work isn't "it can't do this". Let me hazard a guess from what you wrote. The 3-tier spec (design → specs → build details) may be the cause rather than the cure. A big upfront spec has two failure modes the model can't help you with: it can quietly contain contradictions, and it can be ambiguous in ways the model resolves by guessing instead of asking. "Adding clients" is a good example of the trap, even assuming your real spec was more detailed than the comment. "Client" is overloaded — a customer in the domain? An API client? A consumer of a service? And "A clear design requirement was essentially adding clients" is very imprecise: does the model add them, or build a UI so the end user can add them? I know this was just your comment and sorry to sound harsh but if the spec had sentences like that I can definitely see it going off the rails.
Your own conclusion, smaller, concrete units, is the right direction. Except by units I don't mean partitioing the program into smaller units (files, modules). In fact, you should stop thinking about implementation at all. I'm thinking more about the way of asking the LLM to build it. One feature at a time etc. so you can tighten the feedback loop. Then you can early on (in the first hour say): "I also need a way that the user can add/manage clients - basic CRUD" and that small sentence might be enough the model makes it all (UI, API, backend etc.) to enable that and put it in a proper place in the app. A big ambiguous spec defers that discovery to the worst possible moment.
> And "A clear design requirement was essentially adding clients" is very imprecise
That's not a sentence they literally gave the agent. This is their full quote.
> A clear design requirement was essentially adding clients, explained clearly and comprehensively.
Why are you assuming they described this so ambiguously?
> I haven't managed to really figure out what's the best way, but my latest thinking is really having boil down tasks to almost unit operations "add UI button, wire to Api call. End".
And at that point you might as well just code the thing yourself.
The first attempt failed, so they caved in, but they’ll try again after a while and lay those people off again.
The dream of perpetual labor machine is something capitalists are willing to destroy the planet in order to chase their fictitious dream. Oppressors must be stopped.
Don't talk like a perpetual labor machine wouldn't be awesome if you had it.
You just want to make sure you have it, and not your boss using it against you.
There was a reason why the phrase "perpetual" was used, to invoked how unrealistic perpetual energy machines are and how futile it is for the human race to chase such dreams.
How many tens of trillions of capital have been incinerated in reducing the quality of life for workers compared to actually uplifting them?
Sure, you'll need energy inputs, you're not going to beat thermodynamics. But we're not capturing even 0.01% of available energy yet, there's a lot of room to grow.
Industrial capitalism has been fantastic for quality of life. Here I am sitting in an air-conditioned office browsing HN during a workday, instead of slaving away in the fields as a peasant farmer. I'll take more automation please.
Steer towards that Fully-Automated Luxury Communism.
HN prefers FULLY-AUTOMATED POVERTY-STRICKEN HETEROSEXUAL TERRESTRIAL EXPLOITED CAPITALISM
I was wondering the other day why we didn't put this level of effort into building a highway across the Atlantic and the Pacific. It seems to me if we just piled bricks made with all the money dumped into AI in the ocean, we could easily have done this. Likewise we could have just build a canal across the United States from the Atlantic to the Pacific. These efforts would have drastically reduced shipping costs and risks but they look impossible (and stupid) on paper so no one tried them.
Why is AI different?
Because it happens in a computer and many people think that makes something easy, like CGI or computer hacking in movies. It's intangible magic and belief is the product sold to investors.
There are two kinds of knowledge. There is explicit knowledge which can be codified easily in markdown files or a wiki. Then there is tacit knowledge which is mostly encoded in the experience of an organization's individuals. Explicit knowledge is like the tip of a giant institutional knowledge iceberg.
Maybe they could use a distillation process. Have the AI prompt the senior engineers repeatedly (don't do this). Like squeezing the oil from olives!
One of my favorite pieces of writing on this topic
https://books.worksinprogress.co/book/maintenance-of-everyth...
I think that this is doable. Similar to having a new employee shadow a more experienced one and observe, you could implement a sort of program where AI shadows experienced employees and asks questions when they do something it doesn't understand.
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.
> You would literally be spying on employees 24x7 for weeks at a time with the express goal of replacing them someday.
Isn't this almost exactly what Zuck is trying to do at Meta?
https://www.reuters.com/sustainability/boards-policy-regulat...
If so, that's pretty on-brand.
And that tacit knowledge doesn't have easily quantifiable value, it doesn't show up on the P&L so most execs don't consider it. I've seen it time and time again over my career, someone leaves or layoffs happen without considering this and then the company is scrambling to figure out processes that someone was quietly running or maintaining for years that no one else even thought of.
Managers believe in the fungibility of engineers and do not understand the concept of institutional knowledge. Always has been.
How do you fix a Ford ?
Buy a BYD / Xiaomi / Zeekr / Xpeng...
SAd thing is Toyota owns Ford and they have gotten very far from Demming practices
Ford Authority also covered this story: https://fordauthority.com/2026/06/ford-unified-operations-hi...
I have a simple mind. I think of a company with 100 employees building a dozen houses at a time. That company could replace a six-person framing crew with a two-person, one-robot team as an experiment. They could do various experiments to see if there was a better option here. It would be at the expense of four employees.
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.
I feel like "Company ditches staff in favour of AI" stories currently fit into two categories 1) The CEO is actually ditching staff for other reasons like falling revenue, but "going AI first" sounds a lot better 2) The CEO is making a mistake.
My speculation is straightforward: adding “AI” to the sticker ups the share price, dropping headcount improves the balance sheets upping the share price, and doing both at once could be perfect for a CEO bonus or strategic board member sell off.
I was diagnosed with Parkinson disease in 2018, I had tremors and severe muscle weakness, I also had stiffness and balance issues. In 2022, I was introduced to PD-5 Ayurveda treatment program from Limitless Natural Wellness (Go to Limitlessnaturalwellness .com). I read some studies and immediately started on the PD-5 protocol; I noticed changes within months. I noticed the tremors stopped and my mobility improved; the body weakness and balance/gait issues also improved significantly. After completing the treatment, I am happy to report that my Parkinson disease is well under control. I feel very good and energetic these days!
Amongst other things, AI won’t buy cars.
Not yet perhaps.
soon agents will live for us
the ~game~ matrix
The dystopian future where no one owns cars is already being laid.
Cars are more and more becoming white goods appliances with the driving experience becoming less and less a priority. Even enthusiast cars now are about raw numbers and need electronics to reign them in to make useable for the average driver on the average road.
The average user probably doesn’t even want to drive and have AI do it for them.
Repairability is becoming less viable as mechanical parts replaced with screens and digital locks. Parts availability is already an issue, only going to get worse especially with the pace of new cars are being churned out from China.
The end will be car as a subscription. We already have it with leasing, and BMW having to pay to use your electric seats.
> The dystopian future where no one owns cars is already being laid.
Pardon me?
We're living in the dystopian present, where most everyone has a car or several. Cities are crowded with cars -- both moving and parked -- and it's awful for humans who aren't cars.
I can't wait for the moment people switch to a subscription and the cars are shared and drive themselves. The streets will be just as full of moving cars, but at least the parked cars hopefully disappear, giving us more space for trees or sidewalks or anything but cars really.
You are injecting a lot of assumptions and wishful thinking to view the removal of ownership from this equation as a net positive.
I see no reason to assume that this would lead to the disappearance of parked cars or to more trees. Our corporate overlords will want to make use of that space for more cars or infrastructure to support the new car network, why would they ever just give it back willingly?
I think you've misread the parent poster.
* Their "not owning" means a swap to a subscription/license for the car, which could still be exclusive rather than shared.
* Your "not owning" assumes a reduction in the number of cars per capita.
In other words, the "dystopia" they are referring to is one that still has today's problems of gridlock, land use, urban planning, etc., with new kinds of problems layered on. Cars not being user-repairable, being nickel-and-dimed on features, a monopolistic used-parts market, and a general shift towards whatever boosts the car-manufacturer's profit margin.
Probably be used for more ones for cars
TBF, cars are the one device that the anti-ownership movement may have a point.
Why not?
Self-driving cars may have a control agent at the HQ that places car orders as needed.
Everyone thinks AI can do everyone else's job, but not theirs.
This is excellent news. I'm glad some executives are starting to understand that AI will never replace an engineer with knowledge. AI is just a tool that needs guidance. If they put people without knowledge in charge of the machine gun, they will never be able to hit any target. Junior and mid-level engineers will never become super engineers by telling AI, "Just do this."
AI is a great revolutionary tool for work, but it is still a tool and needs humans to drive it. Obviously companies heard the promise of "Replace your large headcount expense with cheap tokens" and creamed their pants. Its funny to see them walk back, it will be at least a few years if not more before it replaces humans fully (and will need another breakthrough)
Back in dot-com, there used to be a website called f'ed company that chronicled the dot-com dead pool. This time around there needs to be a similar website that records AI walk backs so it helps the mgmt class not make stupid decisions.
The folks who make the decision to throw away these engineers in the first place are the ones who should be laid off.
Nice thing about the C-suite is that you get authority and compensation without responsibility. You just claim responsibility when things are good. And when bad, the underlings who have responsibilities but no authority take the heat.
And this is why the C-suite is the single best target for replacement by AI.
The only job AI's are capable are doing is the role of executive. I think we should replace every C-Suiter with AI.
This is going to happen more and more. AI is a tool that should make your employees more efficient not replace them outright. And if it doesn't make your employees better? I guess AI isn't applicable to your business then.
I can see a lot of companies coming to this realization over the coming months and years.
Exactly. Tools by definition have users. LLMs (real things) are tools. AI (science fiction) is a "person". When the "AI" demands a wage, I'll consider it real. Until then it's an LLM which is a tool. You wouldn't replace a plumber with a wrench.
I hope those engineers made Ford pay out the nose.
They did not. I been saying for decades that software devs form a union.
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
You can negotiate your salary even without a union. Also being part of a union doesn't guarantee you won't be laid off because of AI.
A union absolutely can and should protect workers from frivolous layoffs.
If the company tries to layoff 10% "due to AI" the remaining 90% can strike.
History is full of union solidarity vs idiotic management.
I’ve had this happen a few times in the past, back when you’d fire your expensive people and replace them with cheap human labour instead of AI, so I have a word of advice.
Be sure to have “updated your rate schedule” recently, which explains why you’re now twice as expensive as before.
They know how bad they screwed up and how bad they need you now. I’ve never had anybody refuse a giant rate bump now that we were all on the same page.
Over-hiring during the bygone era of free money is now seeing an overcorrection. AI is a true if small part of it, but mainly it’s an excuse that doubles as posturing to the investor hive-mind.
lately I saw a post [1] about Doorman Fallacy [2]. I strongly believe this is another example of that.
[1] https://rozumem.xyz/posts/17
[2] https://en.wikipedia.org/wiki/Doorman_fallacy
Talk about making a huge sale to a car sales-man and totally pawning them. Tech has evolved into next-gen "selling science".
Yeah, but they are short-term re-hires. Once they "get encoded" it will be bye Felica: "Ford just wants to first seasoned engineers walked out before their decades of knowledge could be encoded into automated workflows." https://www.gadgetreview.com/ford-fired-its-best-engineers-l...
Oh grand! And I bet that these rehires are going to be FULLY emotionally invested and fully loyal for the future. just stupid all the way around...
(shooting from the hip) What if the 350 engineers had built a company instead? Union-like efforts could focus on creating new companies (having the "union" is about ensuring a certain level of organizational knowledge, like YCombinator creates a structure around startups)
I think companies would more careful about how fast and lose they operate, if firing may mean having to contract with a 3rd party.
Funny how almost every wave of automation starts the same way: "we're gonna cut headcount," but ends with "we're just shifting roles"
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
Problem with thinking you can replace your employees with AI, this is not the case. This is like thinking you could replace your NASA engineers with IBM computers in the 60s. The AI revolution changes drastically the way people work, and empower them, they multiply their productivity, but they never ever replace domain expertise, and business logic.
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.
corporatism is on equal footing with prosperity gospel.
Yep.
I'm prosperous because god/market deems me worthy.
If they gave the engineers appropriate severance packages, then they're at least out that much as a stupidity tax, but that's probably the most we can expect as far as consequences for the exec suite.
Presumably they're also out the top 10-20% of talent which immediately found jobs elsewhere and would have little interest in returning to Ford to work under such incompetent management.
They could always be hired as contractors at x5 the cost for a fixed contract over 2 years to train the ai.
Wouldn't be a bad deal tbh depending on age and how much you have already for financial independence in retirement.
If my employer offered me a deal that would allow me to retire early, comfortably, to train my AI replacement, I'd take it. If they succeed, well I'd have gotten laid off anyway. If they fail, I get to laugh all the way to the bank with my newly found free time.
Sounds like meta would be just the company for you!
This sentiment feels like a relic of a previous age. Yes _maybe_ but it's also equally likely that the best they laid off was on the ropes for months trying to battle ghost job spam and AI filters. It's almost shaming anyone who isn't hired someone immediately as deficient and "not the best". Honestly the conversation should be focused on how the execs can he made responsible.
That's fair. My intent was not to shame the "bottom 80%" which is of course most people, but rather to make a call for accountability. Like specifically the execs should have to answer to their board not just for the wasted time and severance packages, but also for the cost of losing some staff permanently with these shenanigans.
Im not calling for any action, but that kid doing something about Healthcare CEO - that did help.
How did it help?
It did send a message. If the message was sent on a daily basis this world would look completely different.
I am quite sympathetic to your position. Seeing those who manage to evade accountability consistently paying a heavy personal price was immensely satisfying. But at the same time, I don't think it resulted in any structural changes that minimise the proportion of accountability-evaders plauging society.
Ideally of course everyone, irrespective of any immutable traits they may have, gets to enjoy a healthy, satisfying, and stable life with plently of avenues for upward mobility. Short of that ideal, a society which equally burdens the rich and poor with devastating, seemingly random, unavoidable life-chaning events is decidedly better than one which only affects the poor.
So for these reasons I don't advocate for the actions of "the kid" but I don't think the consequences of his actions were in any way "bad" per se.
Or, if they're anything like me, even if I hadn't yet moved along they'd find that for them my price has gone up in the interim time period.
There is a huge cost for this either way (severance packages, yes, but also lost productivity, reduced team coherence, etc), but that unfortunately doesn’t necessarily translate to a political cost for the managers involved in pushing the dumb idea, particularly if the CEO was pressuring everyone for cost savings. They will escape by saying, “We did it because everyone else is doing it and we were told it was the right thing. How were we to know that it wouldn’t work?”
> We did it because everyone else is doing it and we were told it was the right thing. How were we to know that it wouldn’t work?”
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??"
Boards are usually filled with ex-CEOs who also thought these dumb bets were good
And the board is pulling down $300k per year or more for sitting in maybe 11 meetings per year and participating in a “comp committee” where they just review data and recommendations from comp consultants and agree to whatever the consultants tell them. So, why rock the boat?
> You don't become a pioneer in your industry by just cargo culting everyone else.
You usually don't become a CEO of a long established company by being a pioneer either though...
You may be able to argue this particular case though, as he is a marketing guy and he was a pioneer in marketing as few others capitalized on social media/YouTube when he did.
But I feel like that's completely unrelated to how adjacent that's to what I'd consider a pioneer in a CEO position. Hence me pushing back a lil
Sometimes you do get the CEO gig for being a pioneer, but then the whole organization thwarts whatever you want to do by repeatedly saying “we don’t do it that way here” and dragging their feet until you get fired.
Let’s be honest about how the incentives work at large companies. The CEO probably has a $10m/yr comp package. The EVPs under him are $3m-$5m each. Nobody is really interested in making the company wildly successful, because that would entail lots of risk. Better to just keep everything moving along at the market average, don’t get fired, and collect the package every year. If you’re lucky, you do this for 3-5 years and you collect another $10-$20m termination package when they fire you. Then you hire an executive headhunter to get you the next gig and you repeat it. So, your main goal is to play defense. Don’t do anything risky that would get you fired. Pay McKinsey to bless whatever you want to do and if it blows up, blame them and call Accenture or Deloitte next time. Rotate between management consultants as required. Buy your tech from IBM, because nobody gets fired for buying IBM. Yes, your whole career will be MEH, but you can vacation all the time at your multiple houses in the Hamptons and Italy.
this is the correct take
Why do u even bother about lost productivity. Come on dude how many firings need to happen before one has to see the reality. Just do the minimum job required for the position and move on. Loyalty should be both ways. But that's not the case
There's the added cost that the best people are the least likely to return after a layoff.
And those which return will have zero loyalty to firm.
Once you were dumped for AI gamble, you will never do the extra work, because you will probably be dumped in year or so, when someone else will get same or different stupid idea.
But it's not stupid idea, it's more like desperate attempt to remain in game in competitive market by doing what everyone else does. Idea crafted to final decision by people paid to see a bigger picture ... which unfortunatelly stop seeing smaller things which matters.
Perhaps if the rank and file at a company see personal consequence for those in the topmost posistions (salary deductions, demotions, or firing) in response to such glaring fuck ups that might even help mitigate some of these morale issues.
Well, nothing is B&W. If you penalize people for making some bad decisions, they will not make any decisions.
There's not a single person only making good decisions. Bigger the corp, much harder to keep it successful.
Reason why You and I are not in their position is that we would probably make much more mistakes.
Absolutely. And why would you? Companies spend lots of time talking about loyalty and teamwork, but they show their colors when they do these layoffs. Smaller companies, often still run by the founder, can be much better. The only large company I ever saw command any employee loyalty was Hewlett-Packard when Bill and Dave were still running things. At one point, in the 1970s, they needed to cut payroll by 10%, so they asked the employees: we can cut 10% of the people, or everyone can take a 10% temporary pay cut. The employees voted for the pay cut. So, every other Friday, the company was shut down and everyone, all the way up to the CEO took a 10% pay cut. When times improved, they bumped everyone back up to full pay and moved on. That created huge loyalty. Unfortunately, it didn’t last. Bill and Dave passed the reins to others and eventually HP became like all the other companies and fell apart.
its because CEOs hire mckinsey/deloitte/BCG types for couple millions that give them a 60 slide powerpoint to justify reductions in force.
the same consultants can be blamed if decision backfires
Not really those execs paying that stupidity tax though. They still get their bonuses. Pretty much zero consequences.
If they take the job they likely need to give back some or all of the severance package.
The social contract that American society elect (including these non executive engineers) emphasize career flexibility (right-to-work) and returns of capital than job security. Especially during booming economic years.
I am not sure engineers in say, Europe have any lower career flexibility. It's a false narrative to claim otherwise.
The frustration of being an engineer in Europe comes from the rules that this implies. Well, aside from the fact that this is mostly gone, but still exists in some big public or banking companies.
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)
That's not mandated by law though. Shouldn't companies following such stupidity be easily out-competed by those that don't? In he market for their products/services but also in the market for employment.
This would be true if the government didn’t have ridiculous outdated requirements for starting new companies.
The kinds of companies this is talking about cannot legally be started in France. We're talking about the largest companies:
Credit Agricole, a "cooperative" bank that is ruled by union contracts that impose strict limits on how many commas in the rulebook are allowed to move per decade. A company where any change gets so stuck committees they found it easier to implement changes through parliament than through the company's own management structure. Several times.
Total, government owned oil company that gets special tax treatment and gives free shares to French presidents and ministers who leave office. Actually has a good reputation as an employer, but not because there is any chance in hell of getting promoted.
EDF, the power company (mostly nuclear), who are positively famous in how difficult they are to work with, both internally and externally. But, have a good reputation as an employer.
France Telecom, which used to be a subsidiary of EDF. They split off to remove worker protections from their (many) employees. Still extremely tied to the government. They have an extremely poor reputation as an employer (as in they have driven employees to suicide).
If you try to start any such companies in France, the government is going to outright sabotage you, whatever the laws say.
Career flexibility like Do Not Compete agreements?
Almost nobody is covered by non compete agreements. And if you think you are, you should just ignore it anyway.
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.
Is there any consequence for execs who don't layoff when they are supposed to? You have to look at the situation symmetrically.
Why does it need to be symmetric? There’s no reason we couldn’t decide that we want to err on the side of employing too many people.
We already do with legislation that requires severance packages and tax benefits for hiring. Many countries go much further.
If its not symmetric then you bias towards status quo which is a really bad way to act as a CEO.
> 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.
> If its not symmetric then you bias towards status quo which is a really bad way to act as a CEO.
That doesn’t follow. It could just as easily bias a CEO towards over hiring, or finding ways to retrain existing employees, or any one of a million things that’s not the status quo.
It’s also possible that there currently exists pressure to push CEOs to lay off too many people and a little pressure in the opposite directions puts CEOs in a position where they are free to either layoff or hire as they see fit.
> Yeah that's not how a company should run
That should is attaching a moral judgement to this, and that’s not up to you. Many people think that the one of the primary purposes of a company is to provide employment. Even in the US our system makes it easier to hire someone than it is to fire them.
> Many people think that the one of the primary purposes of a company is to provide employment
This is not good for society.
Go argue with most of the developed world I guess.
This holds true for most of the world. The economy is not a jobs program.
You might not want it to be a jobs program but a portion of the economy is a jobs program. I think you’re just repeating the same thing over and over so you can get the last word in.
> There’s no reason we couldn’t decide that we want to err on the side of employing too many people.
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?
> execs cargo culting on using AI as a pretext for layoffs.
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.
I assume AI lay offs are mostly investor crud anyway. I've never seen them provide any evidence or examples of where AI helped cut those jobs and it always feels like its easier to lie and say you were fired because of AI so that your fired former employees blame AI and not you. Plus, if AI is really making your org more efficient, why aren't you training your employees who are not using it effectively enough? It all smells.
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.
Plus you can't say it's because Trump's terrible economics so safer to blame AI.
I asked a buddy who works at one of the Big 4 and he said its the remnants of the Great Resignation:
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).
The saying used to be "with great risk comes great reward".
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.
Layoffs aren’t “playing with people’s lives”. Employment is only by mutual consent and everyone knows that. Consent can be revoked at any time which is why anyone prudent (especially in a software engineering role) isn’t living paycheck to paycheck.
Don’t blame a customer for the vendor’s irresponsibility.
Unfortunately for this perspective, one side of the equation very much plans their lives around this mutual arrangement. When the other party experiments with the arrangement without deep consideration, I think "playing with people's lives" is very much an apt description.
Just because I would not be destitute tomorrow does not mean that my life (and those of my family) would not be deeply impacted.
That’s true in the US but not in most other rich countries, where there are legal constraints on terminating an employment contract.
That's how it works for every rich/powerful person in every aspect of their lives; maybe to a slightly lesser degree with health.
This is how it has always been? C-suite is incentivized to make big speculative changes; if it goes well, they get credit. If not, oh well.
> Interestingly, there were no consequences for the execs that made this 'mistake'
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 they didn’t get canned, the slap on the wrist is the cost of doing business. If we all agree to investigate ourselves and we’re all very disappointed in what happened, what a shame!
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.
Welcome to the Era of the Business Idiot. People who manage stuff without having even the remotest inkling of what the work is.
Their entire management skill involve the application of one of the following options:
1 - Fire People
2 - Spend Money
3 - Call a meeting
Punishing leadership for perceived strategy mistakes is a great way to scare good leadership away from working for you.
Babying bad leaders who don't take responsibility for their actions is a good way to scare away good employees.
Why are you assuming this? Because Bloomberg didn’t report the execs’ performance reviews? Maybe they did face consequences and we just don’t know.
bad performance review and a layoff are completely different worlds.
Agreed, but what they’ve done isn’t illegal (IANAL). A performance review doesn’t address the irreparable harm these actions may cause.
It is reasonable to assume, that this could be walked back in such a way that no one is held accountable.
> Why are you assuming this? Because Bloomberg didn’t report the execs’ performance reviews? Maybe they did face consequences and we just don’t know.
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.
If you allow a likely guess with no evidence to play the role of fact, you're just as bad as the AIs
America has a convicted felon as president?
That's true, but I literally mentioned the decades of experience we've all lived through, so it's not without data. When the guys who made the bad decisions are still at the company and giving interviews then that's a very strong indicator they're still there and not facing repercussions.
I imagine our current hyper-corporate landscape would have us making that assumption.
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.
It seems that you don't understand governance in corporate America. For some education, read "Barbarians at the Gate".
Conversely, why do you jump to their defence? Large companies treat employees as a cost centre, and if a cheaper alternative becomes available then they're let go. It's not a huge leap of faith to assume so in this case.
The probably got bonus and promoted since they saved company costs!
Consequences for American car executives, are you crazy? Have you seen Stellantis cars recently? Large parts of the US (and European most likely) car industry is driving straight into irrelevance
On the topic of Stellantis, I rented one recently (through no fault of my own) and when I returned it the guy asked me how it was. I told him I wouldn't drive one of those things again if they paid me, and the guy said "yeah we get that a lot, let me get you the discount".
It sounded like they had a "Stellantis discount" for people who said something.
Nice guy, actually.
As far as I can see on Wikipedia page or homepage for Stellantis, they do not make cars under their own name. So, which brand did you rent actually?
Jeep Wagoneer, I just remember the Stellantis logo on the infotainment boot screen. I thought it was a Stellantis Wagoneer because the Jeep logo was almost completely absent, at least in memory.
Thank you. If you don't mind me asking - which part of driving experience made you think "never again"?
Okay so this was actually about a year or two ago, but I remember the infotainment system glitched out a lot for no discernible reason, which prevented me from accessing a lot of the controls, and I had some difficulty with the hardware controls which just felt poorly thought out from a UX standpoint.
Some of the things an owner would obviously get used to, but it felt like you were constantly struggling with it to do simple things that you don't even really notice doing in most vehicles.
The infotainment system was constantly having trouble, like freezing up or just shutting down for no apparent reason and not turning back on. I remember a lot of issues with the backup camera. Not unique for a modern car, but this one had more than its fair share of glitches. I think I had to reset it twice. It also developed an issue (sorry can't recall what it was exactly) that persisted for a day or two which spontaneously resolved itself while I was driving back to the dealership.
I want to say it had hardware AC controls (which is good), but I think I had it for three days and only figured out how to adjust it the way I wanted it on day three. I don't recall if I didn't understand that something was a button, or if a button actually had several different "modes" which weren't readily apparent, like being a combo rocker/push button. Normally these sorts of things are obvious from how the dash is deaigned, but my wife and I took three days to puzzle it out.
There were some other minor problems, but altogether it felt poorly thought out and kind of low quality, which clashed with some of the "luxury" accents my model was equipped with, like wood paneling and the lights which spelled out "WAGONEER" on the ground at night when you opened the door, which felt gimmicky. That money would have been better spent on refining the UX.
I actually don't think it was a bad drive, if you were just driving. I was just constantly frustrated trying to do anything else with it.
Thank you. Reminds me my struggle with a new cellphone about 6 or so years ago (don't remember the brand :(). Random reboots when I was using Maps (a very scary thing when you are driving in a new country), corrupted memory card and lost images, random freezing. Call quality was ok, pictures were so-so, but it is just like you said - things around main function - that's what makes or breaks the experience. On paper the phone looked really good, but the experience as whole was awful. Got back from the trip, returned phone back to Costco...
Stellantis is wild. They went from having a large portfolio of brands, each of which had many popular vehicles in America to having the Chrysler minivan, the Dodge charger, the Jeep Wrangler/Gladiator, and the Ram pickup.
I don't think it's right to categorize "no consequences".
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.
oh poor babies they got sad their human sacrifices didn't work, that's surely as much punishment as losing your livelihood because a pack of morons act randomly based on feels.
Life is not fair and there are no guarantees. It’s a hard phase of realization to go through but life’s surprises are easier to get past once you do.
Just give up any moral responsibility because life is unfair; what great advice!
So give up?
By complaining together, we can create changes that make life more fair.
An excellent argument for advocating to Make the Bastards Pay when they get away with some unfair bullshit.
If the only consequence is that they're not rewarded, then it seems like it's very fair to categorize it as "no consequences".
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)
Generally, you don’t want to punish people for making decisions. At least I don’t. I value people who are willing to try things and I generally believe any decision made in good faith is better than no decision. My litmus test is was it a reasonable decision given the information available at the time in service of a greater goal. I can live with the consequences of that. If it turns out to be a not so great decision then we can fix it. I’m not going to fire someone for the result when the process was sound.
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.
Even from the selfish perspectives of these executives, it can be quite bad to isolate people from the consequences of bad decisions. It will prevent learning from mistakes, and lead to more bad decisions.
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.
If you're unwilling to fall on your sword and face material consequences for decisions that cause quantifiable harm the people who work for you or your customers, you do not belong in a leadership position imho, but that isn't where we are today. The people making these decisions will face no consequences for the harm they cause. Its likely they continue to be employed and receive generous compensation.
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)
Not getting fired is not the same as isolation from consequences. People who make rational decisions and achieve results get opportunities to make more impactful decisions. People who don't get results don't get more opportunities - or maybe find themselves in a situation where the scope of their decisions (and blast radius) is limited. Firing is for misconduct or when someone has no value to offer. It's more of a spectrum than a binary thing.
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.
> People who don't get results don't get more opportunities
This shows to me that you have a lot of faith in these companies that I can't share based on my own experiences.
My experience is more like: the defining characteristics of what gets you more opportunities is personal attachment to the boss. They like you? You get more. The whole performance review culture, as an example, is based around phony justifications around this. They get to re-define what "getting results" means to favor buddies. This is the only determining factor, period, and people come across to me as absurdly foolish when they believe something else.
I don't have faith in these companies. I don't know how they operate. I know how I operate.
We only need to look at the consequences (or lack thereof) from the 2008 financial crisis to understand that there will be no consequences for the corporate class.
Society is incredibly inconsistent on this point. If a CEO shit-cans 500 people who sacrificed future career prospects for the company and end up destitute, society say's that's capitalism and they need to learn to code in a month or something. If a stay at home wife gets "bored" and divorces her husband of 20 years, he commonly owes her a decade+ of alimony to "make up for the sacrifice and time to get on her feet" or some such.
As usual it's communism for the plebs and something entirely different for the capital wielding class.
> As usual it's communism for the plebs and something entirely different for the capital wielding class.
Bad example. Ask Bezos how much he paid his wife after the divorce.
It's a good point, the counterpoint is, he really only had to cushion the post-association lifestyle of one of thousands whom became dependent on his amazon business, a tiny fraction. A typical pleb will be held to cushion the lifestyle of nearly everyone who depends on their paycheck if someone decides to terminate the relationship (usually, their spouse and kids -- in USA this doesn't extend to elderly parents though it does in some other countries).
I don’t think society is a monolith. Many of those who support your proverbial alimony are also against CEOs acting with impunity.
Sure, but the interest of "society" is what judges typically claim to represent when they bang that gavil.
If you wish to change it to "the law of society" which is what "society" backs with violence, go for it.
A job doesn't usually involve a lifetime contract. And if it does, the severance required had better be incredible.
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.
I'm not sure how on earth you could consider marriage a lifetime contract when it's no-fault divorce at any second. The divorce process is at-will, though it takes some time to finalize.
While I agree that you don't want to punish people for making bad decisions, I do think there should be a carveout for when those decisions impact people's lives.
Yeah they didn’t like… migrate them to bad software they had to undo or something. They laid off hundreds of people due to overhyped products/trend chasing.
Lots of decisions impact lives. Some are literally life and death decisions. Sometimes the best decision possible with the information available at the time is going to turn out badly. Or maybe a bad decision achieves a good result.
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.
IMO that’s what used to be “accountability”, especially for decision makers.
> Generally, you don’t want to punish people for making decisions.
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.
It's easy to take that stance in jest .. when it has no material impact on you. But if your life was uprooted by the decision of an executive because they made what was a "good faith" decision for the benefit of the shareholder, then I'd wager you may feel differently.
My life already was uprooted by those exact decisions... A couple times... The first guy fucked up so badly that every last one of us lost our jobs, including him. He was an unqualified moron who weaseled his way into a position where his bad decisions had major consequences. It was extremely frustrating. It happens. It will happen again. That's life.
“Consequences for mistakes” is generally not a good way of operating. Kind of the whole idea behind a blameless retro for example.
Execs are paid an extraordinary amount of money because they are the ultimate decision makers and should be responsible for their decisions.
So they should get paid lots of money to never do anything risky?
Sometimes things don’t work out. That doesn’t mean it was a punishable offense to try.
Seems like this is a theme in our culture, maybe it's a world wide trend. The underlying theme I notice is unaccountability and selective application of rules, laws, norms to some people and not others. It seems to me like people with power, and in leadership positions like executives, get to create an environment where they are able to continually extract from a mass of people.
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.
I don't know about you, but if I was fired to be replaced by AI and then my employer came crawling, back tail between their legs, I'm pretty sure I'd start negotiations at an extra zero at the end of my salary.
There never are. Those are going to be viewed as two discreet successful interventions.
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
That's because the company likely doesn't view it as a mistake. The executives did their job: they tried something the company likely considered reasonable (or even strategically necessary) and pivoted based on results. At the executive level, that's not considered a blunder. What counts as a blunder would be (1) being too cautious to try a change, then falling behind your competitors if that change turned out to be critical or successful; (2) attempting at change, seeing that it didn't work, and refusing to pivot or falling prey to the sunk cost fallacy.
I have mostly enjoyed AI programming and I do like using Codex. The truth is that it sometimes makes me more way more productive, but not usually. Many days are spent writing specs and babysitting prompts and it can suck. Even expensive Codex 5.4/5.5 with high thinking writes code that is just ... lazy. It takes a lot of work to get it to write excellent code. It's definitely a full time job all by itself.
I'm not talking about rocket scientist code either - I'm talking about things using raw for( instead of range-based for, or writing code that is absolutely fucking riddled with imperative logic, hacks, and kludges, when something should clearly be data-driven. Stuff that is so bad I have to tell it to start over. It routinely designs amazing architecture and absolute shit architecture, sometimes on the same day. It's just so weirdly inconsistent. If you ask it to fix a bug then you have to double check if it used a hack and sometimes it will admit to it. Sometimes it lies.
I just do not see how AI is going to replace large numbers of seasoned engineers. That would be a disaster for companies that try it. Could it replace large numbers of juniors? Yes. And maybe I am being fantastically naive. I'm 100% willing to concede that it's possible or even likely.
While being slow to pass judgment or disregard an approach is a valuable trait in a senior Eng, I think 3 years is plenty of time to wait for proof of concept to pan out. It’s not panning out, it doesn’t seem on the verge of panning out, and soon the real cost is going to be passed on and the subsidies will end. LLMs see ripe to be the new IDEs, but not the new Engineers
> Artificial intelligence is a fantastic tool, but it’s only as good as the information you use to train it
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.
The impression I'm getting over this huge number of AI roll backs is that AI is useful in some circumstances, but it's just not a cure-all. It is expensive, and increasingly so, straining the ROI scenario. My expectation is that the use-case for successful AI implementations is ultimately going to be narrow.
I do wonder if the rehiring was just at a lower compensation level.
"Welcome back, you are now two levels down"
This is what we are finding a lot with the "AI normies". Because the AI responses are so confident new users of it think it must be correct.
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.
The world might slowly realize that a lot of generative goodness and direction is the result of our limitations and constraints as builders, not necessarily our velocity.
The article is not about generative AI at all.
They will try it again next year, after they slap an AI camera on the rehired people.
So "AGI" was not found internally at Ford and they didn't know they needed actual engineers to keep the lights on?
It's OK to just say that the plan was to rehire back the engineers for far less compensation.
[dupe] https://news.ycombinator.com/item?id=48674446
Tune your bot, this is the 3rd time (at least) you've duped this dupe and deleted. You still have this:
https://news.ycombinator.com/item?id=48704222
> while some workers will also help improve and train the AI systems
Our AI sucked but that doesn't mean less AI. We need better AI, not humans.
* Backfired * :-D
This doesn't seem like it backfired. Firing these people and rehiring a fraction of them catapulted Ford to the top. In fact, these roles were apparently there for over a decade before modern AI even came to exist and Ford was never top. This actually presents a formula for improved reliability - fire almost everyone, then hire back the cadre with value. A very DOGE-esque approach and I'm surprised it worked.
The best people are the least likely to come back, and going through all of that will surely impact productivity.
Just two days ago at work a call of 15+ people spent a non-trivial amount of time recounting the scars of colleagues being laid off, or they themselves having to sign severance papers, only to be saved in the final hours. These events happened 10-15 years ago and they still cost the company time a decade later, not to mention that trust that erodes with these events.
If companies want people to focus on work, those people need to feel secure in their jobs. Laying them off and hiring them back is not job security. It’s a signal that management has no idea what they’re doing. Why would these people follow the leadership of those who can’t even solve the issue of staffing without making a mess of it?
It’s also bad when seemingly competent employees are laid off while incompetent ones stick around. It sends a signal that it doesn’t matter what you do, so why try.
Well, the fact is that it seems to have improved productivity. While we can theorycraft in many ways, the reality appears to have been that firing everyone and bringing back a select few takes you to heights you could never reach for 16 years prior.
The gray beards were always least threatened by AI. It’s the junior market that’s getting decimated.
Predictably, now office workers and engineers (including here) will say "What I always knew - LLM's can't think, be creative, don't have nuance. My job is safe!". I predict the article will be quoted again and again at lunch tables and family gatherings. However, one should be especially careful when something confirms ones own biases.
Firstly, the "AI" discussed here is not LLM's. They are talking about visual quality inspection systems. There's been many other articles in the press: Ford's new quality automation is computer-vision defect inspection, built on IBM's visual-inspection tech, iPhones photographing parts on the line, running since 2020. By most reporting it works fine, pushing detection rates from ~70% manual to 99%+. This is classical CNN at work doing the job of quality inspectors... completely unrelated to desk-work by an engineer or what LLM's do... yet that's exactly the inference the headline invites (and many here in the comments seem to be making).
The timing only underlines it: rehiring is presented as the cleanup. Apparently the rehirings started 3 years ago, so whatever it's undoing is older still and therefore unlikely to be LLM driven. While ChatGPT did come out 3.5 years ago it seems doubtful someone would fire people left and right the moment they saw the first ChatGPT... only to then regret almost it immedaitely and rehire them - all within the span of 6 months.
This further supports that the article is about years-old automation bet being quietly unwound, and is completely unrelated to mainstream discussion about AI and jobs today.
Also, 350 rehires is just noise. Ford is shedding thousands right now: plant pauses, battery-plant retooling, projected restructuring in the 8–13k range.
Finally, as always with corporate announcements... ask why an internal staffing decision is even a press story. To me this feels like PR (a nice feel good story that ties into to a subject people discuss a lot now). It takes the sting out of all their announced layoffs. There's probably also internal company politics to it (someone suggested rehirings and now want to say 'see what a great idea this was' and maxx it out).
Tangential, what is this "JD Power Initial Quality Survey" flaunted in this article?
Problems reported in the first 90 days of ownership. Overwhelming minor niggling complaints like a piece of trim making a noise or even just misunderstandings about systems.
American automakers love crowing about that survey because it's easy to do well on. And then the car falls to shit six months later, but hey, it held together for the first 90 days so all good.
A survey is sent to car buyers with a huge number of questions related to their satisfaction. Automakers, Tier-1 suppliers, and probably others get to buy this data to mine for market research.
At a past role with a Tier-1, we bought part of the dataset. A quick regression showed that satisfaction was strongly correlated with buyer age, and there was very little signal otherwise. (Young people with overtime work and daycare pickups don't respond to surveys unless they have a serious axe to grind while retirees aren't so constrained)
Translated: This AI is still undercooked, it need more humans to train it, so we can fire them again.
Interesting as companies like Ford like to show they’re on the leading edge of AI, but do they really have the capabilities and 10x 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.
The Porsche 911 is pretty reliable, it's basically the same car they've made for over 50 years so they've got it figured out.
This seems like a totally crazy statement. The only common thing that a current and 50-year-old 911 share is that there are six holes in the engine block.
And the engine is behind the rear axle.
Maybe... but the re-hiring probably involved very substantial salary raises for the re-hirees.
An expensive process.
I've had two different Porsches, a Cayman S and a Macan. Neither gave me a day of trouble. You just have to do all the maintenance, which is obviously expensive.
porsche is part of volkswagen, so it's not that surprising that they're decently reliable. i probably see 10 porsches for every ferrari, lamborghini, etc that i see, and i think a large part of that is reliability - even absurdly rich people don't want to deal with an unreliable car when there is a more reliable alternative.
I wonder if Porsche is allowed to exist in point where they are not fully cost optimised so there is more spend on those slight things that keep reliability. Most other large manufacturer cars seem to be cost optimised while least amount of that is carried over to customers...
I hope they got themselves a nice pay raise in the process. Ford will can them again as soon as it can.
amazing, the same company that says people should not be allowed to repair their own vehicles. henry ford is rolling in his grave.
I've lost my ability to believe that things will feel 'normal' at work.
I no longer want to make connection with any coworkers.
If AI thinks so much faster than humans. does it age fater than humans? and in that case, does AI have dementia already?
They should charge at least 30% more because now they know that they can't keep production going
Were these engineers fired and replaced with AI? Article implies they brought back retired engineers.
So...don't buy any Ford vehicles designed and/or manufactured in the last 8 months or so?
I wonder which of the management consulting companies caused this fire/rehire experiment.
It's not like those consultants recommended something the CEO and Board didn't want to hear. They are paid to be the shield that blocks the arrows from shareholders. If they can get paid twice, once to recommend laying off 350 engineers and again to later recommend refilling 350 engineers all the better.
Whoopsie, quick, let's boost our quarterly bonus by 50% for being bold and experimental.
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.
Sorry but this reeks of marketing. To what extent was Ford actually attempting to replace these engineers with AI tools in the last three years or were they just letting them go by attrition? Was this the result of an actual AI influenced layoff? I read both the Verge and the Bloomberg piece and none of this seems to be articulated but it sure does seem to capture a vibe right now that companies are footgunning themselves all over the place with LLMs, despite no evidence of this being related to any of that...
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…
I hope those engineers demanded 2x higher salaries this time.
And they just go back to work like nothing happened?
That's the interesting question. Are expert engineers willing to go back after being treated that way or knowing what happened to others?
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.
> 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.
> 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.
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?
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"
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..)
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.
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.
Ray tracing says hello.
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.)
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
Obviously. It was the goal of automation since its inception: reduce human involvement.
This was too predictable! Maybe one day AI can wholesale replace roles, but not yet. If anything, we need more seasoned people that are experienced enough to steer AI and find mistakes it makes.
Even when AI gets better, we will always need people who can troubleshoot AI itself.
foot, meet gun
What does it mean to “train the AI”?
> 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.
Had a couple of Taurusii back in the day. 100% ended up having a problem where the power steering pump shit the bed because a plastic piece in the pressurized side failed. Paid to repair one, oem pump broke on drive home due to same plastic piece under pressure.
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.
I had a Focus in the 2000's that was the most reliable car I ever owned. Rust got it eventually but it still started instantly at any temperature and ran like a new car.
If I had a nickel for every broken focus door handle I've fixed... (There's a weak pin that always breaks.)
LOL yeah I had that too. Forgot about it. Cheap fix was an aftermarket door handle from Amazon or RockAuto or someplace like that.
I'm not saying it was a perfect car. The interior was cheap, the sheet metal seemed to be recycled tin cans, and it definitely showed its age by the time I got rid of it. But that engine and drivetrain seemed to be bulletproof.
Yeah, the engine and drivetrains are immortal, everything else is constantly dying though.
It was also designed by European engineers, not in Michigan. Not saying that's the reason the Focus is more reliable than a Taurus but they didn't follow the "typical" Ford design process at the time for that vehicle. For what it is worth I owned a 1992 Taurus and it left me stranded more times than I can count. Just some of the issues I had were a water pump that exploded and a seized A/C compressor.
<eyes roll in literal loop>
Pretty much everything Ford brings to the US that was designed in Europe is loathed by anyone who has to own it out of warranty.
Turns out that when you have a building full of engineers in Germany or England their domestic engineering culture results in work output not all that different from the sort of stuff people chastise BMW and Land Rover for.
That said, the Escort, and to a lesser extent the Focus, are generally considered very good vehicles.
> <eyes roll in literal loop>
k
Ford invested heavily in reliability in the late 2000s - see e.g. https://www.latimes.com/business/la-xpm-2012-apr-15-la-fi-bo...
Step 1: fire everyone. Step 2: figure out how to use AI.
In that order, apparently.
Alternatively:
Step 1: 30 minute conversation with AI on how to use AI. Step 2: fire everyone.
I don't understand why Ford did not just put the LLM on a PiP.
Of course in that order!
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!
This idea is everywhere right now, that AI is some magic black box that will solve all your business problems. The sentiment is spreading through the exec team where I work now too. It's like a disease.
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.
> 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.
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.
I think you are misleading people by calling it a "hype cycle". There is no going back from this technology. It is going to encroach every part of lives more and more.
What does hype even mean concretely? I think this is just a coping mechanism if you ask me.
Hype cycle doesn’t imply the technology has no value. But we should be able to talk about it as the boring, nerdy technology it is without that whole doom trolling and “AI will literally solve everything”
> the boring, nerdy technology it is
Er, what? Intricacies of a transformer pipeline might be boring and nerdy, but the results are not. BTW, I've yet to find any strong argument on why the current ML approaches are bounded below the level you find appropriate to be bored.
“Hype Cycle” is a Gartner term of art, which they use to describe the way waves of technological innovation penetrate the business world:
https://www.gartner.com/en/research/methodologies/gartner-hy...
The idea is there’s a rush of irrational exuberance when an “innovation trigger” makes a new toy looks promising, and everybody rushes to use it for everything, regardless of whether its suitability-for-purpose is proven. Inevitably many of those pioneers find that it’s not good for their particular problems after all; usage reaches a “peak of inflated expectations,” and crashes into a “trough of disillusionment.”
Then the tech enters a quieter and more gradual “slope of enlightenment” as people work out use cases where the tech actually adds value; then adoption reaches a “plateau of productivity.”
Worth a glance at the way they map this to prior waves of technological exuberance.
Motte and Bailey.
From your video, it looks like your definition of hype involves a situation where eventual adoption increases above what is in the hype today.
Here's what the parent comment thinks:
> 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.
Obviously the parent doesn't think of hype the way you think of it because they claim that big data was pointless -- they don't see the eventual "slope of enlightenment". They think of hype cycle in the colloquial way and I was responding to that.
I see this all the time in the website and frankly the patronising "but actually hype means something else" is pointless and pedantic. I urge you to respond to words within the context and not bringing in academic definitions.
I'll thank you to not put words in my mouth ;).
I think the tech is useful, but the hype is ridiculous so I expect lots of companies to have large share price declines et al when this settles.
Big data also had a good core, but all the e-commerce sites building a data lake wasted lots of money.
The person I replied to put words in your mouth. You and I agree what you meant. You mean that the hype would die down and won’t come back up again. Ever. So reply to the person above who thinks you mean hype this way.
Whoops. Apologies, bad sleep last night and replied in wrong thread
AI is particularly infectious among C suites, because AI is great at spewing words. A substantial portion of folks in those positions are there because of family connections, existing wealth, etc., and their only contribution to the business is similarly spewing words. They went to good colleges where they excelled at spewing words. They worked cushy / hard jobs where they had to spew the just the right normal predictable words for this context, perhaps at a large volume and with little notice... and the words were hard words... not known to those outside the industry.
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.
Its ideology.
> 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.
They also don’t seem to realize the AI might take over highly paid executive positions before skilled work.
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.
is this why some people say if your anti-ai your basically the anti-christ? i've never understood the connection to that.
"Line must go up, forever."
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.
> 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.
And that's how you get a new war. Line must go up isn't only for the corps, its for US GOV debt too. Interest payments are already close to $1 trillion. As soon as GDP growth doesn't stay ahead of the compounding interest, the music stops. The line must go up or you get a sovereign deb crisis. When all other avenues are expended, the gov must force the economy to expand by any means necessary. Historically, that meant war.
Government debt can go down too. Democrat governments have been historically pretty good at balancing the budgets - only for their Republican successors to waste all of the effort on tax cuts for the rich and, yes, yet another dipshit war.
Your way of writing is nice.
> 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.
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
If you are incapable of doing more than "spring init my_app" then the current models are like magic.
> 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.
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.
Well, the business plan came out of this mysterious box, after we fed in the payroll reduction requirement...
Earlier this year I’ve been in calls with leaders from top US companies where their strategy was basically “we have to switch absolutely everything to agentic right now, otherwise we are dead”. That was the full thought.
That made reading their subsequent layoff blog posts pretty depressing
Top men.
I would literally be homeless before I went back to a company that fired me to replace me with AI, then asked me to come back.
How about if they doubled your previous salary?
I guess the crux of the issue is that there's no guarantee that the company would not find a different, equally harebrained, reason to lay GP off.
There's no guarantee in any job that you won't be laid off.
True, but if you already know that a given company tends to fire on a whim, you'd be excused to feel a little bit distrustful.
For how long?
I wouldn't go back, regardless of salary offer, unless I didn't have any other jobs lined up. If I'm not employed than any job (even a bad one) beats being unemployed. But if I was employed, I wouldn't go back to a job where they laid me off for stupid reasons, no matter how much money they offered.
Or maybe people just have bills to pay and/or want to support their families. A little critical thinking and empathy goes a long way...
When you first lose everything, in the process you end up having to pawn expensive principles like that, so when other things like this happen, it's easy to seize the opportunity.
Were you ever homeless and starving?
I doubt it :)
Doesn't seem bad to me. Come back for a pay bump and get paid while you search for a new job.
As a homeless person, do not wish homelessness on yourself.
Oh how the wheels have turned.
Why are American tech-bros such loud-mouthed bullshitters ?
Reminds me of this disaster at Toyota,
https://www.wsj.com/business/autos/toyota-bet-technology-wov...
American tech is basically a sales machine. An ounce of tech will be coated with a ton of selling force. Everything in America is a business, presentation or a talk-show - including government, education, relationships. People do selling and faking to themselves sometimes.
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.
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.
Cope
What exactly am I coping with here?
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)
All the people happy about this are just holding back the progress of our species smh.
won’t someone think of the lightcone!
Do we have any hard data about AI improving any business metrics yet? I am not skeptical that it might, but I have yet to see anything.
they should try and replace some executives with AI, seems like there is way more room for improvement there.
arguably one of the best cases for AI, it can definitely spin anything to shareholders
Maybe not.
You're absolutely right, Charles Schwab, we should cut 10% of our workforce tomorrow!
At the very least they should be held accountable for their actions. Weird how ruining people's lives is rewarded and celebrated with bonuses.
It makes sense if ruining lives is good for the company, firing and layoffs that are /necessary/ are hard for anyone with empathy. They should be rewarded for doing that.
That’s very appealing, the problem is the prompts control the results to such a degree, the person composing the prompts are the executives and at that point, you have not done anything.
Management at these USA companies could give zero fucks about you.
It’s a disease that has spread throughout all of capitalism.
But that’s USA 250 years.
As opposed to? The government? union leaders? Nobody really cares about you, unless you are a friend or your family.
The only job AI's can really replace are in the C-Suite.
Not a great time to be middle manager
I don't know, middle management is all about people and project management, and I don't think AI is displacing that.
Quite frankly I’m enjoying the schadenfreude on this one.
I'd rather not have a vibe coded car.
AI is here to stay. Like it or not.
We will still see several reports of over adoption, mistakes, regression… all will only serve to learn, refine, and hopefully regulate.
I think it’s pretty naive to expect the entire world will simply discard the technology and go back to having humans doing it all.
The value of the ai firms isn’t in building a useful tool to increase productivity of your staff by 20%. It’s not an electric drill.
It’s to replace 99% of your staff. In every industry.
Ai will be a useful tool, but either companies like OpenAI are massively overvalued or the economy will completely vanish at a high speed and their valuation will be meaningless.