4 ms·

GenAI at fault, and nothing to do with amazon laying off 30k people and having an overall shitty culture where people mostly don’t want to stay?

jiggawatts 7mo ago
Also, managers are incentivised to force AI onto the remaining staff to “boost productivity” but of course they won’t accept any of the responsibility or blame for that decision.
- zihotki 7mo ago
  Just tell the employees to make AI fully adopted in SDLC and make it secure and reliable. Don't make mistakes. If it works for models, why not humans? /s
aerhardt 7mo ago
Maybe both, and possibly other causes too, but allow us a moment to revel in the schadenfreude of AI code slop at hyperscale, will you?
deleted 7mo ago
[deleted]
applfanboysbgon 7mo ago
> GenAI at fault, and nothing to do with amazon laying off 30k people GenAI is literally the direct reasoning they used for laying off 30k people. > “As we roll out more Generative AI and agents, it should change the way our work is done. We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs,” [Amazon CEO Andy Jassy] bluntly admitted.
- spwa4 7mo ago
  There is a long history of people blaming AI for not being able something totally unfair and me and I do believe quite a lot of probably somewhat older ML practitioners are seriously tired of that constantly happening. Amazon is prioritizing investment into data center expansion over paying employees. And ML ... is present in the building, and about as involved in the firings as the cleaning staff is, only people are scared of AI and so it gets blamed for everything. The firings are driven by imho misguided financial engineering, and it sure as hell is not being being done by ML. But what is reported? Management firing people? ML. Engineering screwing up the uptime? ML. Someone screws up their job? ML. Don't you know? ML is killing people in Iran today. Not mullahs. Not the military. ML. Obviously that's where the responsibility lies ... Usually blaming ML is like suddenly coming up with conspiracy theories like here, or impossible suddenly added requirements, and usually utterly ridiculous ones (like criticizing Deep Blue for not being able to play poker, yes I realize I'm old, but it's a bit like criticizing the very best competition canoe on the planet for it's disappointing spaceflight capabilities) Like here: large blast radius AI-assisted outages ... we've all written software, and we all know the problem here: THEIR TESTS SUCK. Probably because they fired all the good SREs for insisting software teams spend time on tests, or demanding integration test failures are fixed before shipping the software. By the way: I'd like to point out that in most/all industries where jobs are lost on a large scale the situation is like the Amazon situation: ML is not even remotely involved. So while I get the criticism, it doesn't work like that. The Auto industry first got blasted with very traditional engineering, which worked and depended on very old style mathematics. What's happening in factory automation is 99.9% 3d geometry (to the point that ML, is actually a simplification of the problem). Then the auto industry got blasted with what every industry got blasted with: stuck in demand-limited markets. Every car company can easily build 10x more cars next year, but there's no point: nobody will buy them. So the only thing worth doing for these companies is to produce cheaper ... and that means getting rid of people (when end-to-end taxes on income in Europe are 60-85% and actually rising). With only a few exceptions, these companies find ML too expensive for projects. So while I understand "we're defending our jobs", it's misguided ... the big job losses in the west have nothing to do with ML. MAYBE those are coming, but large job losses have been predicted in the last 50 AI "revolutions". 49 times that was wrong. And the actual problem is really a return to 99.9% of history: when it comes to doing what is needed to keep society going 10%, maybe even 1% of people can do it. That means you need something for the other 90% or 99% to do. The solution is the only thing that has helped in the past: having the government put on huge public works. From building the pyramids to the Sagrada Familia (and yes, wars. But let's please not do that), or ridiculous engineering projects like Europe and America's rail networks. There's a stable in the Italian alps that has a private rail connection. So fix the problem. I don't know: build a large cathedral in Washington or something. Hell, hire people to make sure it has a depiction of the last supper where every square micrometer of the painting was designed by an AI with 1000-member engineering team, so people can spend their entire life looking at the painting with a microscope and find new details every day. Let's do something "great", in the sense of an enormous effort. Fly 100 missions to Alpha Centauri. Fix the demand-limited issue the economy has. "Do more with more". And stop blaming ML. Hell, I'm currently in an old European city filled with 200-year old buildings. Quaint. Cool. Except ... not really. 90% of these buildings suck. Can we just rebuild 95% of ... all European capitals? Every building that is way too old and has no reason whatsoever to be preserved other than it's currently slightly cheaper ... can we please just rebuild them better? Do stuff like that.
- surgical_fire 7mo ago
  It's not, and in the latest round of 14k people laid off they were more transparent that it was a result of previously having overhired.
  - malfist 7mo ago
    > previously having overhired Funny way of saying that Jassy told people he doesn't like the culture of a larger amazon. Also, if we overhired in 2020-2022, why the hell are we still correcting it in 2026? Did none of the layoffs in 2023 on do the job? Just an all around failure of leadership with no ownership.
    - surgical_fire 7mo ago
      Oh believe me, I am not defending the prick. We are in a thread of Amazon holding engineering meetings after AI-related outages after laying off 30k people. If anything this highlights gross incompetence of a moronic leadership. It should be them being laid off. If overhiring indeed happened, it is also a failure of leadership. Hiring too many people and then firing a bunch of people causes friction, loss of knowledge, decreased morale, etc.
      - malfist 7mo ago
        But like, what if we did the layoffs bit by bit and tell people each time there will be more and stay tuned. Surely that's a sign of strong leadership. Just like "muscle confusion" for workouts! Can't let people feel to safe or stable.
    - keeda 7mo ago
      > Did none of the layoffs in 2023 on do the job? No, because the calculus of layoffs shifted. Briefly, there is always a natural attrition rate A%, but whenever companies do an X% layoff they expect a smaller Y% additional attrition (due to morale etc.) So they expect an overall (A + X + Y)% reduction in headcount within a few months of the layoffs. However, the job market swung so rapidly from pro-employee to pro-employer in that timeframe that the Y% never happened, and in fact there was even a drop in A%. And so companies still ended up with more employees than planned and had to scramble to achieve their headcount goals using other means (RTO mandates, shifting headcount offshore, further layoffs with AI washing, etc.) A bit more detail on the calculus in this comment: https://news.ycombinator.com/item?id=46142948 https://news.ycombinator.com/item?id=46142948
nixass 7mo ago
Absolutely correct. Now let's drop anothet few billions to make AI better and avoid such mistakes in the future. And we might lay off some more folks to make room in a budget for more AI
cratermoon 7mo ago
Those two facts are not mutually exclusive. Laying off 30K people and pushing the remaining engineers to use the ensloppenator for everything, this is the expected result.

jiggawatts 7mo ago

Also, managers are incentivised to force AI onto the remaining staff to “boost productivity” but of course they won’t accept any of the responsibility or blame for that decision.

zihotki 7mo ago
Just tell the employees to make AI fully adopted in SDLC and make it secure and reliable. Don't make mistakes. If it works for models, why not humans? /s

aerhardt 7mo ago

Maybe both, and possibly other causes too, but allow us a moment to revel in the schadenfreude of AI code slop at hyperscale, will you?

deleted 7mo ago

[deleted]

applfanboysbgon 7mo ago

> GenAI at fault, and nothing to do with amazon laying off 30k people GenAI is literally the direct reasoning they used for laying off 30k people. > “As we roll out more Generative AI and agents, it should change the way our work is done. We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs,” [Amazon CEO Andy Jassy] bluntly admitted.

spwa4 7mo ago
There is a long history of people blaming AI for not being able something totally unfair and me and I do believe quite a lot of probably somewhat older ML practitioners are seriously tired of that constantly happening. Amazon is prioritizing investment into data center expansion over paying employees. And ML ... is present in the building, and about as involved in the firings as the cleaning staff is, only people are scared of AI and so it gets blamed for everything. The firings are driven by imho misguided financial engineering, and it sure as hell is not being being done by ML. But what is reported? Management firing people? ML. Engineering screwing up the uptime? ML. Someone screws up their job? ML. Don't you know? ML is killing people in Iran today. Not mullahs. Not the military. ML. Obviously that's where the responsibility lies ... Usually blaming ML is like suddenly coming up with conspiracy theories like here, or impossible suddenly added requirements, and usually utterly ridiculous ones (like criticizing Deep Blue for not being able to play poker, yes I realize I'm old, but it's a bit like criticizing the very best competition canoe on the planet for it's disappointing spaceflight capabilities) Like here: large blast radius AI-assisted outages ... we've all written software, and we all know the problem here: THEIR TESTS SUCK. Probably because they fired all the good SREs for insisting software teams spend time on tests, or demanding integration test failures are fixed before shipping the software. By the way: I'd like to point out that in most/all industries where jobs are lost on a large scale the situation is like the Amazon situation: ML is not even remotely involved. So while I get the criticism, it doesn't work like that. The Auto industry first got blasted with very traditional engineering, which worked and depended on very old style mathematics. What's happening in factory automation is 99.9% 3d geometry (to the point that ML, is actually a simplification of the problem). Then the auto industry got blasted with what every industry got blasted with: stuck in demand-limited markets. Every car company can easily build 10x more cars next year, but there's no point: nobody will buy them. So the only thing worth doing for these companies is to produce cheaper ... and that means getting rid of people (when end-to-end taxes on income in Europe are 60-85% and actually rising). With only a few exceptions, these companies find ML too expensive for projects. So while I understand "we're defending our jobs", it's misguided ... the big job losses in the west have nothing to do with ML. MAYBE those are coming, but large job losses have been predicted in the last 50 AI "revolutions". 49 times that was wrong. And the actual problem is really a return to 99.9% of history: when it comes to doing what is needed to keep society going 10%, maybe even 1% of people can do it. That means you need something for the other 90% or 99% to do. The solution is the only thing that has helped in the past: having the government put on huge public works. From building the pyramids to the Sagrada Familia (and yes, wars. But let's please not do that), or ridiculous engineering projects like Europe and America's rail networks. There's a stable in the Italian alps that has a private rail connection. So fix the problem. I don't know: build a large cathedral in Washington or something. Hell, hire people to make sure it has a depiction of the last supper where every square micrometer of the painting was designed by an AI with 1000-member engineering team, so people can spend their entire life looking at the painting with a microscope and find new details every day. Let's do something "great", in the sense of an enormous effort. Fly 100 missions to Alpha Centauri. Fix the demand-limited issue the economy has. "Do more with more". And stop blaming ML. Hell, I'm currently in an old European city filled with 200-year old buildings. Quaint. Cool. Except ... not really. 90% of these buildings suck. Can we just rebuild 95% of ... all European capitals? Every building that is way too old and has no reason whatsoever to be preserved other than it's currently slightly cheaper ... can we please just rebuild them better? Do stuff like that.
surgical_fire 7mo ago
It's not, and in the latest round of 14k people laid off they were more transparent that it was a result of previously having overhired.
- malfist 7mo ago
  > previously having overhired Funny way of saying that Jassy told people he doesn't like the culture of a larger amazon. Also, if we overhired in 2020-2022, why the hell are we still correcting it in 2026? Did none of the layoffs in 2023 on do the job? Just an all around failure of leadership with no ownership.
  - surgical_fire 7mo ago
    Oh believe me, I am not defending the prick. We are in a thread of Amazon holding engineering meetings after AI-related outages after laying off 30k people. If anything this highlights gross incompetence of a moronic leadership. It should be them being laid off. If overhiring indeed happened, it is also a failure of leadership. Hiring too many people and then firing a bunch of people causes friction, loss of knowledge, decreased morale, etc.
    - malfist 7mo ago
      But like, what if we did the layoffs bit by bit and tell people each time there will be more and stay tuned. Surely that's a sign of strong leadership. Just like "muscle confusion" for workouts! Can't let people feel to safe or stable.
  - keeda 7mo ago
    > Did none of the layoffs in 2023 on do the job? No, because the calculus of layoffs shifted. Briefly, there is always a natural attrition rate A%, but whenever companies do an X% layoff they expect a smaller Y% additional attrition (due to morale etc.) So they expect an overall (A + X + Y)% reduction in headcount within a few months of the layoffs. However, the job market swung so rapidly from pro-employee to pro-employer in that timeframe that the Y% never happened, and in fact there was even a drop in A%. And so companies still ended up with more employees than planned and had to scramble to achieve their headcount goals using other means (RTO mandates, shifting headcount offshore, further layoffs with AI washing, etc.) A bit more detail on the calculus in this comment: https://news.ycombinator.com/item?id=46142948 https://news.ycombinator.com/item?id=46142948

nixass 7mo ago

Absolutely correct. Now let's drop anothet few billions to make AI better and avoid such mistakes in the future. And we might lay off some more folks to make room in a budget for more AI

cratermoon 7mo ago

Those two facts are not mutually exclusive. Laying off 30K people and pushing the remaining engineers to use the ensloppenator for everything, this is the expected result.