For example, there was a case of how Claude Code uses React to figure out what to render in the terminal and that in itself causes latency and its devs lament how they have "only" 16.7 ms to achieve 60 FPS. On a terminal. That can do way more than that since its inception. Primeagen shows an example [0] of how even the most terminal change filled applications run much faster such that there is no need to diff anything, just display the new change!
It's not even that performance is unimportant in absolute terms, but rather that the general state of software is so abysmal that performance is the least of your problems as a user, so you're not going to get excited over it.
The people that could make terminal stuff super fast at low level are retired on an island, dead, or don't have the other specialties required by companies like this, and users don't care as much about 16.7ms on a terminal when the thing is building their app 10x faster so the trade off is obvious.
If the results are expected to be really good, people will wait a seriously long time.
That’s why engineers move on to the next feature as soon as the thing is working - people simply don’t care if it could be faster, as long as it’s not too slow.
It doesn’t matter what’s technically possible- in fact, a computer that works too fast might be viewed as suspicious. Taking a while to give a result is a kind of proof of work.
In recent times I found myself falling for this preconception when a LLM starts to spit text just a couple of seconds after a complex request.
The cause of that is the companies with the big models are actually in the token selling business, marketing their models as all around problem solvers and life improvers.
It contains a helpful insight that there are multiple modes in which to approach LLMs, and that helps explain the massive disparity of outcomes using them.
Off topic: This article is dated "Feb 2nd" but the footer says "2025". I assume that's a legacy generated footer and it's meant to be 2026?
Today the same argument is rehashed - it's outrageous that VS Code uses 1 GB of RAM, when Sublime Text works perfectly in a tiny 128 MB.
But notice that the tiny/optimized/good-behaviour of today, 128 MB, is 30 times larger than the outrageous decadent amount from Wirth's time.
If you told Wirth "hold my bear", my text-editor needs 128 MB he would just not comprehend such a concept, it would seem like you have no idea what numbers mean in programming.
I can't wait for the day when programmers 20 years from now will talk about the amazingly optimized editors of today - VS Code, which lived in a tiny 1 GB of RAM.
Not that everything we want an agent to do is easy to express as a program, but we do know what computers are classically good at. If you had to bet on a correct outcome, would you rather an AI model sort 5000 numbers "in its head" or write a program to do the sort and execute that program?
I'd think this is obvious, but I see people professionally inserting AI models in very weird places these days, just to say they are a GenAI adopter.
Maybe one day that will change