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You can use as many different apps for yourself but good luck sustaining a community/team/org that requires learning 5 apps for participation, especially when not all users are savvy.

In order to sustain an ecosystem instead of mega-app, that ecosystem needs to be really smoothly integrated, and I know of no good examples of this

Regardless how you edit/compile your code, you still need to debug/troubleshoot problems in production, and that is very likely to use Kubernetes. So the more reasonable approach seems to be: first, figure out how do you troubleshoot/identify/mitigate a problem in production, then reproduce it in development environment and work to fix it at daytime. When you have instrumented your app for reasonable debugging experience then using these tools on development machine becomes much easier problem, K8s or not.

I did designs that overstayed their intended lifespan by 15 years. I did designs that were cancelled even before being fully implemented. Most however had their predictable lifespan of 3-6 years.

It seems to me that the key is to make useful product based on sound technical decisions; entropy (a thing you can't control) will handle the rest.

DIY is good if this is part of your life plan. Otherwise it's a distraction.

We live in civilization for a reason; different people specialize in different tasks so that overall, we all can enjoy our lives more.

In other words, except for simple little things, don't make me fix my bathroom: there are people who do this faster and better than me, but NO ONE is going to fix bugs in my software for me. To each his own.

The flip side of minimum wage is often overlooked: people on the bottom end of the spectrum, who struggle to compete with other minimum-wagers, are cut out of the workforce. At $15 or $20/hour, the job requirements are higher than at $10/hour, and these folks stand no chance.

Likewise, the low-end employers are priced out of the market.

It's the same survival of fittest, except the weakest constituance is hurt most. They are very sparse so their voice is never heard.

People are focusing on verbage and precision, but are missing the point.

Having a well-maintained Python tooling is essential for _any_ company who does AI. While smaller companies can get away with open source solutions, for bigger companies it is unavoidable to have teams dedicated to maintaining and supporting Python tooling.

This announcement is troubling, and may indicate one of the two: 1) Google is in dire situation, and there is no more fat to cut, so they are starting to cut muscle. 2) Google management is clueless and cannot discriminate between fat and muscle.

I would think about more practical ways to reduce cost fuel consumption. We are still 10-15 years away from practical fusion. We have been, for the last 50 years.

As for Germany, maybe it would make more sense not to hastily shut down nuclear reactors, in favor of coal and gas, or at least until the equivalent capacity of renewable energy is online, if they really cared about the environment?

What you really get from IDE is higher productivity, based on a sample of few hundred people I've worked with. It won't make bad engineers good or vice versa, it would just make everyone more productive.

If I were hiring an engineer who claimed not to use IDE on principle, I would be very careful and maybe even suspicious: a craftsman who doesn't care about using best tools for the job, may have problems.

, and so are doctors, and bankers, and some education administrators, and high-ranking public servants, and even some university professors,and the list goes on.

There is a multi-year process of training and selection. You need to take risks and invest and learn to bend your mind in certain ways. Some people cannot bear this, or just bored out of their minds and cannot continue and get back to living their "normal" lives with less risk of depression or mental breakdown.

Those who survive, make decent money, and some even more than decent money.

So what's wrong with this picture?

It can be even simpler with intervals: 1 is a half-tone, 2 is a whole tone

Major scale: 2 2 1 2 2 2 1 Minor scale: 2 1 2 2 1 2 2 etc

They sum up to 12 (octave)

Now that you got the theory, practice playing them evenly from every note and make sure they sound right.

Fingerings are a separate story though.

While I understand the borrow concept, I can't see how it is useful here. Returns come from your doing something, not from not doing something. Deciding what actions would bring best returns is the essence of planning. What's special about tech debt in this picture, vs for example product features you delay for few cycles later?

The article sounds over-engineered. Tech debt is a term that helps to explain to the management why you are working on improving the internals of the system instead of adding features. You manage tech debt just like any other work item in the backlog: prioritize and execute, or delete. What else am I missing?

Dirty laundry is never an asset.

I don't buy this story as written. It's totally unimaginable that a random dude in a Volkswagen (identifiable by everyone as a foreigner) would gather useful intelligence by making outside photos of random buildings; nobody would let a Volkswagen near anything resembling a military object. As Makinen is quoted himself, there is more to the story.

The only weirder story I know of is the one of Mathias Rust (https://en.wikipedia.org/wiki/Mathias_Rust) .

My personal experience: if espresso machine is 100 then Wacaco Minipresso would be 93, Moka 53, Airpress 52, anything else <50. This is assuming same beans.

As other people mentioned, beans quality is important. Assuming freshly roasted and ground beans are 100, freshly ground 1-month old roast is 50 and 1 month old grind is 25