There are distributions like CasaOS and TrueNAS Scale that try to offer at least a bit of graphical guidance for some popular apps.
Otherwise, you're jumping into the server pool, Windows doesn't really work that different from Linux in that area (in the sense that you can just click on things).
Well, kind of. But there are countless ways to be wrong.
I wonder if the "oh fuck, I don't know what to do and this will definitely crash and burn" feeling ever goes away.
I'm only a relatively new senior, and everyone's looking at me like I know what I'm doing, while I'm internally screaming and trying to juggle code reviews, documentation, ticket management, management management, client communication and 56 other things.
There isn't really a good way to even define for diversity.
The bad approach is the corporate token diversity, where every picture has to include a white, a black and an asian person, at least 50% have to be women and one of them has to wear a hijab. That might include many groups, but isn't really representative.
You could also use the "blind test" approach many tech solutions are using, where you simply leave out any hints to cultural background, but as has been shown, if the underlying data is biased, AIs will find that (for example by devaluing certain zip codes).
And of course there's the "equal opportunity" approach, where you try to represent the relevant groups in your selection like they are in the underlying population, but that is essentially *-ism by another name.
Is it because the peasants hate our freedom and want to destroy our dividends?
Would be interesting to choose bottom of the barrel and average Joe control groups.
Here again, I think, is a somewhat tech-centric view on economics.
There is only a finite amount of automation demand, simply because human labor exists.
Inside of our tech bubble, automation simply means more "functionality" per person per time unit. What took 10 devs a year yesterday can be done by 5 people in 6 months today. That's all five and dandy, but at some point, software clashes with the hard reality of physics. Software doesn't produce anything, it's often just an enabler for physical production. Lube, or grease.
Now, that production obviously can be automated tremendously as well, but with diminishing returns. Each generation of automation is harder than the one before. And each generation has to compete with a guy in Vietnam/Kenia/Mexico. And each generation also has to compete with its own costs.
Why do you think, chips are so incredibly expensive lately? RND costs are going through the roof, production equipment is getting harder and harder to produce, and due to the time pressure, you have to squeeze out as much money as possible out of your equipment. So prices go up. But that can't go on forever, at Stone point the customers can't justify/afford the expense. So there's a kind of feedback loop.
Those jobs, or better, this kind of task, won't go away. It will just become different.
Think about how completely different our modern development looks compared to, say, the 80s. Nobody writes assembly anymore, so nobody learns the basics! Nobody reads the manual anymore, instead we use autocomplete and Google. Remembering the arcane runes of C used to be exactly the kind of "hazing grunt work" you're talking about. That skill used to be valuable, but who of us can honestly say to remember more than a handful of nontrivial method signatures?
That depends on the Western support.
The West as a whole always made sure to send just enough for Ukraine not to lose.
The whole summer offensive debacle last year was caused (to a large degree) by the Western reluctance to send modern tanks, IFVs, etc. So the Russians dug in like hell.
If Ukraine had just Bradleys, not even tanks, at the end of 2022, they could have thrown Russia almost to its border.
At least from a German standpoint I can say: we never had stockpiles. Like literally. The official estimate was that the Bundeswehr had ammo for two days of war. No hyperbole.
The most efficient thing Germany could have done with all the Leopards would have been to use them as mobile roadblocks.
How much coding work is left to be done? Infinity.
Well, no. That's just plain wrong. There is only a certain amount of demand for software, like for every other product or service. That's literally economy 101.
AI doesn't make us 30% more efficient.
You don't know that. Think about how much time you spend on boilerplating. Not only the "traditional" boilerplate, but maintenance, regular updates, breaking upgrades for dependencies, documentation.
Think about search. Google isn't that good at actually understanding what you want to find, an AI might find that one obscure blog post from 5 years ago. But in 10s, not 10h.
Think about all the tests, that you write, that are super obvious. Testing for http 500 handling, etc.
A technology doesn't have to replace you to make you more efficient, just taking some work off your shoulders can boost productivity.
Isn't docker swarm dead?