I'm not sure, it might have changed since, but my personal experience was different.
Tried using zed on Linux (pop os, Nvidia) several months ago, was terribly slow, ~1s to open right click context window.
I've spent some time debugging this, and turns out that my GPU drivers are not the best with my current pop os release, but I still don't understand how it might take so long and how GPU is related to right clicking.
Switched back to emacs, love every second. :)
I'm not sure if title referring to actual development speed or the editor performance.
p.s. I play top games on Linux, all is fine with my GPU & drivers.
I also tried Zed on Linux a few months back, and had GPU/driver issues, so it was either slow or didn't run. Tried it just now and it worked right out of the box, and it's incredibly fast.
I will keep playing around with it to see if it's worth switching (from JetBrains WebStorm).
(Emphasis mine)
This has been the biggest pain point for me, and the frustrating part is that you might not even realize you're leading it a particular way at all. I mean it makes sense with how LLMs work, but a single word used in a vague enough way is enough to skew the results in a bad direction, sometimes contrary to what you actually wanted to do, which can lead you down rabbit holes of wrongness. By the time you realize, you're deep in the sludge of haphazardly thrown-together code that sorta kinda barely works. Almost like human language is very vague and non-specific, which is why we invented formal languages with rules that allow for preciseness in the first place...
Anecdotally, I've felt my skills quickly regressing because of AI tooling. I had a moment where I'd reach out to it for every small task from laziness, but when I took a real step back I started realizing I'm not really even saving myself all that much time, and even worse is that I'm tiring myself out way quicker because I was reading through dozens or hundreds of lines of code, thinking about how the AI got it wrong, correcting it etc. I haven't measured, but I feel like in grand totality, I've wasted much more time than I potentially saved with AI tooling.
I think the true problem is that AI is genuinely useful for many tasks, but there are 2 camps of people using it. There are the people using it for complex tasks where small mistakes quickly add up, and then the other camp (in my experience mostly the managerial types) see it shit out 200 lines of code they don't understand, and in their mind this translates to a finished product because the TODO app that barely works is good enough for an "MVP" that they can point to and say "See, it can generate this, that means it can also do your job just as easily!".
To intercept the usual comments that are no doubt going to come flooding in about me using it wrong or trying the wrong model or whatever, please read through my old comment [1] for more context on my experience with these tools.
[1] https://news.ycombinator.com/item?id=44055448
I've read you comment about all the things you tried, and it seems you have much broader experience with LLMs than I do. But I didn't see this technique mentioned, so leaving this here in case it helps someone else :).