It's simply muscle memory. You think of the action and your fingers do it faster than you can consciously think of where they need to go. But I also use a split ergonomic keyboard (the Iris) and have symbols accessible from home row behind a layer. Though I can switch to a standard keyboard as needed too.

Been using it for all of my software development for the last 10 years. It's fantastic.

That's what happens when you start using LLMs for all of your software development. Garbage code all day long.

Because they vibe code the shit out of everything now. Insane shit is bound to happen.

Oh for sure, it's definitely less common, though there are a number of other companies running it in production as well. This isn't my first Haskell job, after all. My last job was also a similar size company and codebase. Facebook was even running it for a while for their sizeable abusive content detection system before that was shuttered due to company politics/policies (back when they were trying to do something about it at all).

But yeah, it's not the first pick for a lot of companies, though I tend to think of that as a simple mindshare/inertia explanation than anything inherent to the language/ecosystem.

I'm not entirely sure what the Haskell comment is supposed to mean. Just that it would be cool? Or that it would be hard?

Because if it's the latter, that's just really not true. Haskell's quite well-suited to writing web servers and has many high-quality libraries for it. I'd actually argue that it's one of the best options for it in 2025. I write Haskell professionally developing web servers we use for our web and mobile apps. We have about 0.5 million lines of Haskell in production (and given how terse Haskell is, you could expect that size to be at least double were it written in an imperative language).

Nothing about this usage is reasonable. It is detrimental in every conceivable way: https://arxiv.org/abs/2506.08872.

That's what I do, but I really wish I could tell them to fuck off with that shit.

Heh, guilty. Pretty much always something where I had an ambition to make a change but got distracted or didn't have time to work on it.

They aren't useful now, but even assuming they were, the fundamental issue is that it's extremely expensive to train and run them, and there is no current inkling of a business model where they actually make sense, financially. You would need to charge far more than what people could actually afford to pay to make them anywhere near profitable. Every AI company is burning through cash at an insane rate. When the bubble pops and the money runs out, no one will want to train and host them anymore for commercial purposes.

LLMs do not understand anything. There is no semantic understanding whatsoever. It is merely stochastic generation of tokens according to a probability distribution derived from linguistic correlations in its training data.

Also, it is incredibly common for engineers at businesses to have their engineers write code to automate away boilerplate and otherwise inefficient processes. Nowhere did I say that automation must always be done via open source tooling (though that is certainly preferable when possible, of course).

What do you think people and businesses were doing before all of this LLM insanity? Exactly what I'm describing. It's hardly novel or even interesting.

All of that can be automated with tools built for the task. None of this is actually that hard to solve at all. We should automate away pain points instead of boiling the world in the hopes that a linguistic, stochastic model can just so happen to accurately predictively generate the tokens you want in order to save a few fucking hours.

The hubris around this whole topic is astounding to me.