There's no reason for software to be slow anymore

They can probably hire them, and they'd get PIP'd for not jumping when management says jump.

Toxic corporate culture can go a long way to self-sabotage.

No. They want the AI to do it.

The software model has to however be easy for agents to debug in a loop, then it works very well. I recently got Fable to take a desktop app (AzWriter[1] - screenshot Mac: https://imgur.com/31DBG04 + Linux https://imgur.com/1IavBvS) from about 150 Mb -> 80 - 90 Mb on a reasonably complex UI (around 40 pages of text, paginated, etc.), even beating KWrite (160Mb even on KDE, even though KWrite doesn't do pagination or complex text layout, was a surprise to me).

What was important for this was the fact that I can run JSON-defined e2e tests[2], also good to find frame-based leaks, stale-ID problems and general "program shows its using lots of memory in the task manager" (task managers are wildly inaccurate for this, as I found out).

So, I can just tell it "okay, loop this e2e.json test over and over again, use heaptrack, samply, find out why and exactly where it's slow, memory-hungry - find the section in the codebase, figure out a solution" and then let it run overnight. The biggest difficulty here is that many perf tools are still written for humans and that things like "how much memory are we using" is a wildly complex topic (lots of problems actually getting the correct number without over-allocation, memory allocator slack, OS-level page size, memory fragmentation, etc.).

But Fable was able to track down things like "LCD font hinting causes 90k allocations that are unnecessary", etc. etc. - which then also improve frame time, usually. Memory optimization + better perf pretty much go hand in hand (less allocations = more perf). I could track them down manually probably, but it would take way more time.

Having some basic understanding of data-oriented design, cache locality, memory tiering (L1/L2/L3/main RAM), does massively help with architecture decisions (e.g. Azul can use a single buffer for the entire DOM node list, in difference to normal browsers which do the more "object based" allocation model, which massively helped page breaking performance on html-to-pdf use cases[3]). Pure-functional style also helps (f(State) -> UI) because then it gets very easy to drill down exactly where things are slow and where caches are needed.

[1] https://azul.rs/ui/release/0.2.0#demos

[2] https://github.com/fschutt/azul/blob/master/e2e/css-anim-per...

[3] https://github.com/fschutt/azul/blob/master/layout/benches/f...

Note: UI Toolkit is still very WIP, docs + code are still slop, etc. - working on it. But I just wanted to add this.

This is an incomplete and quite superficial view of what is going on out there, in my opinion. I've worked on plenty of projects where the assumption was that since the round-trip to the server is going to take almost 100ms that'll dwarf anything that's going to happen on the server itself, justifying poor choices that lead to potentially adding a whopping 100ms onto that number. These numbers only get larger with a larger perceived "Nothing we can do about it" budget as well, programmers often feel justified in doing just about anything once round-trip time grows, not understanding that they're just adding to an already existing problem.

On top of that: Creating software that isn't outright wasteful in terms of performance isn't even hard, it's just a matter of not doing ridiculously dumb things. The problem I've observed in teams I've worked with is that the majority of programmers don't even know what the dumb things are, and wouldn't know how to even approach making something that's halfway fast.

Edit:

Unfortunately I think posts like these are only going to make the problem worse, because now people are going to ask for voodoo solutions to performance issues, when the answer to their problems was usually just "Maybe stop creating wasteful intermediate structures and just walk an array like a sane person" in 99% of cases. The first leg of any optimization journey in the average programmer's code will likely net tens or hundreds of times faster code, and that's actually all people were asking for.

The knowledge required to make those changes and understand them is fairly minimal, but the kinds of people who have to create spinners for webmail interfaces, have their application add 150ms on top of whatever round-trip you have for processing things counted in 5 digits, etc., have never bothered to even learn those things.

I agree and see this as a side effect of a subtler thing. As people shall be replacable, software is designed and subtly mimics the organization's communication patterns. Features are cut up into the tiniest pieces with clear separation from the start (at least its claimed), and over time whatever change or feature seems overly complicated, won't be done or won't be done in a sane manner because its uneconomical.

You are starting to get software with ticket driven development layered around glue code for existing libraries. I see no problem with libraries, it is just the architecture and vertical understanding that leaves a lot of performance on the table, because refactoring insanity takes resources and a lot of talking, understanding and convincing to be done.

Doing this across big teams starts to have downsides. So one team doesn't have a particular use case implemented or understood it and does not want to support it and you run code to compensate for this.

Best example in a monolith case is oracle...