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.