I don't know how they perceive the performance. I see 41 network requests. That's 2.1 MB of CSS over the wire, blocking rendering and hurting painting and loading speed. There's 400 KB of Tailwind, 87 KB of general CSS, plus another 200 KB of other general CSS. They need to embrace functional CSS properly. I'm sure they could have a single CSS file under 80 KB that renders everything.
These type of comments often come from a place of arm-chair reasoning where you might not sit on the experience of working hands-on in a large team on a large product. While it’s probably true that X kB sufficient, that amount of performance optimisation is usually not warranted at this scale. Maintaining a design system, working with scoped classes, legacy code, and dealing with the complexities of chunking and probably further challenges we are not aware of from the outside. It seems like a common sentiment on HN (maybe not you in particular) is that engineers should drop everything and work overtime on optimizing performance, when it comes to web apps
Performance is not complicated. You measure something and compare the numbers. Through my career I have encountered the following failures repeatedly:
* The complete inability to measure things. This is common among people with low social intelligence. Many people in this line of work cannot measure things and form all kinds of bullshit excuses. Cannot do it all as if they are disabled. Sometimes it is laziness, sometimes it’s autism masking, and sometimes it’s stupidity/ignorance where they believe they shouldn’t have to or are superior from convention alone.
* The shitty team argument. It’s common for people to intentionally avoid or discard measures because there is fear superior performance may indicate an operating deficit. The last thing anybody in software wants is to change approach if they are on a shitty team, because corporate developers are allergic to training people. This is often justified by asking what happens if you work on a team or about new hires.
* Throwing performance data away and lying about it. This is very common when performance data provides evidence that current conventions or favorite tools harm performance. If, for example querySelectors measure 100,000 times slower than some other approaches developers will pretend the performance evidence just doesn’t exist.
* Guessing. When people suck at what they do they invent their own performance realities. When people guess at software performance they are supremely wrong more than 80% of the time and tend to be wrong by multiple orders of magnitude.
They are not generalizations. They are frequently repeated observations. The ability to operate from evidence is what determines if you are working with real professionals or children pretenders.
meerita · · focus · HN ↗
karolusrex · · focus · HN ↗
austin-cheney · · focus · HN ↗
Performance is not complicated. You measure something and compare the numbers. Through my career I have encountered the following failures repeatedly:
* The complete inability to measure things. This is common among people with low social intelligence. Many people in this line of work cannot measure things and form all kinds of bullshit excuses. Cannot do it all as if they are disabled. Sometimes it is laziness, sometimes it’s autism masking, and sometimes it’s stupidity/ignorance where they believe they shouldn’t have to or are superior from convention alone.
* The shitty team argument. It’s common for people to intentionally avoid or discard measures because there is fear superior performance may indicate an operating deficit. The last thing anybody in software wants is to change approach if they are on a shitty team, because corporate developers are allergic to training people. This is often justified by asking what happens if you work on a team or about new hires.
* Throwing performance data away and lying about it. This is very common when performance data provides evidence that current conventions or favorite tools harm performance. If, for example querySelectors measure 100,000 times slower than some other approaches developers will pretend the performance evidence just doesn’t exist.
* Guessing. When people suck at what they do they invent their own performance realities. When people guess at software performance they are supremely wrong more than 80% of the time and tend to be wrong by multiple orders of magnitude.
catlifeonmars · · focus · HN ↗
For example:
> performance is not complicated
Not to mention all your assumptions about the motivations of people who don’t do optimization well. That one can’t possibly generalize.
austin-cheney · · focus · HN ↗
catlifeonmars · · focus · HN ↗