I think you're overall point is correct, but the specifics about twitter are backwards. Twitter would have been way better off using Cassandra (but it wasn't built yet!), instead you're 100% right, they did their own bespoke stack, trying to replicate what google had internally, and they didn't have the $$$ to do it.
It was Facebook/Meta that later open sourced Cassandra and a buncha other great open source stuff.
My advice is to earnestly try your best without compromising your health or mental health, and then mercilessly advertise doing so.
What I mean by that is, try to peek at emails/chat when you can, and send a message. Let folks know when you're having a rough day but ALSO when you're going to power through and show up to a meeting.
Try to do a good job and go overboard on advertising you are working to make up the times you can't be around due to your medical treatments.
You want people to root for you, both for your health, and for your success at the company. Sometimes it doesn't take much for a boss to recognize "oh, they're trying to do a little extra".
Anyone Google has hired in the last ~8 years was hired onto a team that is growing and has a culture of shipping and producing. Google regularly weeds out low performers, be it new grads or long timers who started doing the rest and vest thing.
Now, I don't think most people at google are literally driving to the office or sleeping there most of the time, you'll certainly have more WLB than xAI.
I'd even say, Google is much better at calibrating the right amount to push people than some other companies.
> 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.
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.)
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.
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.
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.
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.
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
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.
Definitely interesting idea given how lockstep parties operate. Ostensibly representatives should be uh, representing local interests, over party, but we've seen this isn't the case.
So if one side is claiming something, yes, would absolutely love to see how much of their net worth is tied into betting that something would come to fruition (like lowering inflation, or medical care, or increasing jobs, etc)
Yes, it's a lot of fun. I'm working on a core team at Google, and honestly i'd keep doing it even if I had 10M stashed away.
It is also very stressful and frustrating at times.
However, early in my career I had challenging and stressful jobs with shitty managers who always tried to crack the whip, where I made 80k a year.
Now at least my stressful job has me pampered between stresses and mostly my boss telling me I did a good job (with occasional critical feedback on how to improve).
It's not an easy job though. I see a fair amount of coworkers counting their pennies so they can quit. Honestly I think you have to be a little bit crazy and enjoy tangly stressful problems to like this job.
If you don't like messing with tech, digging in, feeling confused and lost for hours and days before an 'aha' moment, then its' going to seem like a slog.
It was Facebook/Meta that later open sourced Cassandra and a buncha other great open source stuff.
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