Ryan Peterman

And their conclusion is 70%, or maybe more.

Maybe it's 90%.

I forget the numbers.

You basically have no reason you needed to do this.

Almost never do you need this.

But you actually pay an enormous overhead cost for having agreed to do this.

And a good example, let's say in Python also,

In Python, you can manipulate the symbol table using functions in the inspect module.

And so what that means is you can never be sure of what something's bound to.

You always have to be afraid and check.

And just sort of general, the lack of invariance, that's what makes a language fast.

It's like you have lots of invariance.

What makes your language slow is you have lots of stuff you might have to go confirm at runtime.

And R is just incredibly pervasively like this.

Really what drove me nuts was there were just a ton of people

fundamentally wanted to be professors or postdocs and were in a PhD program.

And they were like, well, if I fail out, I'll go into industry.

And this like, one is that you would interact with people during interviews who like clearly didn't want to be there, just like so unambiguously did not want to be there and clearly viewed this as like a failure that they were interviewing.

And you're like, well, that's not really like a positive sign that we want to hire someone who like doesn't seem like they're going to enjoy the job.

But in addition, a bunch of people, and this is what drove me so insane, because I think it's like all parties involved in the academic system hurt students doing this, is that like so many people just assume that when they finally decided to get an industry position, it was going to be trivial.