Yes! There are still dumb-as-hell companies that can't imagine an app running in anything except Excel (god love 'em), and writing .NET is a PITA for Office. And VBA is dumb.
There's proactive and reactive aggression. Proactive aggression is the typical bullying of others based on what programming they do. It's basically just another way to pat yourself on the back, and people eat that shit up.
What's problematic is that the more jumping you do to avoid dumb workplaces, the greater the possibility that only dumb workplaces will be desperate to hire you.
It's a no-win situation. Unless, of course, you can do a better job of evaluating a job before you take it. But people need to pay rent, and heck yeah, companies straight-up lie about the jobs they offer.
Perhaps it's time for hiring companies to consider that even though employees are discouraged from saying negative things about a former employer, that sometimes yeah, that former employer was a jerk royale.
Wow. After all the truth that's come out which makes everyone else look like a turd (especially Reddit's own users), you still can't find no love for Pao? Ask your doctor if reality is right for you.
But code is written in an entirely pragmatic environment. That means its value changes with time.
But we don't treat novels as pragmatically. If all its references are out of date, we simply excuse that problem by saying the book exists in history. Also, we don't have people running around re-writing novels. I don't doubt for a moment that Kafka's works could be improved if it was "open-sourced" and edited collectively.
And fiction is "code" for humans. The basic design of a human doesn't change nearly at all compared to computers. So instead of optimizing novels for humans with new features or faster processing, we hang on to some of them because particular "code" or life lessons need to be learned by a new generation.
I really wish more help from human-computer interaction & cognitive psychologists would be used to design a programming language.
The programming language is (to me) the most expensive part of a system, because it determines how the coder works & interacts with the system. And the human resources involved in building the system are the most expensive (besides those used to maintain and run it daily).
There must be symbols used to write code that are more easy to cognitively process than others. There must be keywords that are easier to memorize than others. There must be ways to write a statement that are less prone to error than others. Let's start working on this important and neglected problem.
I lived through Statistics, Business Analysis, Decision Analytics, Data Analytics, Data Mining now Data Science. Same thing renamed over and over again.
Regarding post above, it's right. Data scientist is someone better at statistics (classical stats, bayesian, machine learning) than computer scientist, and better at programming (SQL, R/Python for building models) than academic statistician. Plus a teaspoon of visualization (ggplot or d3).
AI has gone through the same sort of buzzword treadmill and even programming in general. Only after living through a few cycles does it really become obvious how cyclic these sorts of trends are.
I'm trying to work on being less jaded about it, and not letting my annoyance with the-new-trendy-thing-that-i-remember-doing-years-ago-under-a-different-name get in the way of learning new technology and new lessons.
