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I honestly don't think you have to do any of those things. You don't need to blog or contribute to OSS or write code on the weekends. I've never had a hiring manager care about any of it. Most just care that you can get along with other people and solve problems relevant to the job. Which is really another way of saying they want well adjusted people.

You can do all those things as well but most people won't care. Blogging and pushing code to GitHub has helped me become a better programmer but it has not directly helped me get jobs.

I get all the other adjectives but where is the elegance?

But you see how you are making my point. Mathematicians as a bunch are very creative and precise at the same time. Going back to my point about the article setting up a false dichotomy. Mathematicians study formal systems which are as precise a thing as humans have managed to make so far. Even if their initial exploration of new territory is not precise it is always in the context of formal systems.

I think the problem is the article is trying to put vaguely defined terms on some spectrum and the tension he is talking about is just an artefact of his own special mapping. Really there is no tension and this mapping is not canonical because the terms are not well-defined. So comparing accuracy, creativity, etc. on a single spectrum doesn't make sense. Mathematics being an existence proof that you can do both things at the same time.

Any sophisticated enough type system contains an ad-hoc, informally-specified, bug-ridden, slow implementation of half of Prolog.

Not just visually. It is also conceptually much more aesthetically pleasant. I still don't know how metaclasses, descriptors, __magic__ methods, multiple inheritance, all the different string formatting schemes, generators/co-routines, etc. work in Python. The amount of stuff you have to learn in Python is a lot more than in Ruby.

New rule. Any sufficiently advanced type system is an ad-hoc re-implementation of Prolog. Once you have unification and backtracking you basically have Prolog and can implement whatever Turing machine you want with the type system.

> When I was a teenager, I got a Dreamhost account and learned web development by uploading PHP scripts and refreshing the page until I got what I wanted. The world of transpilers and SPAs has robbed beginners of this simple experience.

This is the thing that makes me angry the most. We started with interpreted languages with fast feedback loops and then "real" software engineers got into the game and turned all these interpreted languages with fast feedback loops into "compiled" messes with nightmarish debugging experiences.

Fast feedback loops and obvious debugging trails should be a feature that more people pay attention to and the more layers you add the less likely you are to have either one.

So? The planet has also gone through several extinction events. The white knighting ain't helping anyone. Obtuse or not.

I look forward to the day when every software developer has half a clue about monitoring, logging, high availability, configuration management, orchestration/scheduling, performance tuning, build/deployment pipelines, data management/archiving, security and exploit mitigation, etc.

The full-stack developer like the serverless/ops-less future is a pipe dream. Most technology organizations barely even know how to build the software to begin with let alone figure out the right way to operate it.

These d-wave guys are the greatest scam geniuses in history. First they make a "quantum computer" and now they're building trainable exo-suits. I don't even know where they come up with this stuff.

They said availability was "death of a child", not dropping log messages. The trade-off they've made here in terms of being available with some potential loss of visibility is the right one. The system overall is clearly simpler and simpler systems have simpler failure modes and so it is easier to add mitigation components on top that can recover from those failure modes to guarantee higher uptime.

I've never heard anyone say managing a production Kafka cluster was easy or simple. Well, anyone who has had to actually maintain such clusters hasn't said it anyway.