For some of us here, it's just what we love to do, no matter what tooling is available. When I first started building my own software long time ago, it was a very slow Basic and fast raw machine codes (in octal system, PDP-11 like CPU). I enjoyed it not because of tooling, but despite of it.

Over the years, the tooling was getting better in general, which allowed us to build increasingly more complex systems.

With AI, we will still be creating & debugging. It's just that before AI, I had to spend 90% of my work on mechanical not-so-fun things to get things to work, and only 10% on fun algorithmic-intensive parts. But with AI tools, this ratio seems to change, and all kind of boilerplate code & algorithms can be written much faster by AI, hopefully leaving more time for us to work on creative part of the work.

there're different dimensions for "scale" - like handling large monorepos, orders of magnitude more commits, tighter requirements for latencies (for agentic use, e.g. for agentic history navigation)...

Just give people some benefit of doubt. There're much simpler ways to explain certain things that suspecting some universal evil in every move...

Most of the glitches I heard with OpenAI's Voice were not WebRTC related - but rather, to my ear, they sounded more like realtime issues with their inference - which is a very different component to optimize.

It may just be that ROI doesn't make sense: very few user out there truly care about (or even understand) E2EE, for quite some users it creates an inconvenience & support incidents (harder to move from device to device, forgot your passphrase - lost your history, new joiners to a group chat don't see previous history, etc), it requires a significant additional engineering effort to just maintain it, many new features get shipped much slower because of it...

Having seen multiple leading messaging/VoIP stacks from inside, the amount of engineering spent to work around various limitations of E2EE in real prod scenarios is insane, and even for simple every-day-use features metrics don't compare to the metrics of the same feature running without E2EE.

Matches with my experience with Opus for C++.

C# results are empty - @gertlabs - any ETA for those?

It’s very delicious.

I was ecstatic when I found it quite a few years ago in a regular store. A Norwegian friend of mine used to send me a brick of this cheese once a year for Christmas, when I was a student, and I treasured it as one of the most valuable possessions :)

Also, fun fact - the reason this cheese tastes sweet is due to caramelization - the milk gets boiled for a long time (hours) to get the brown color and sweetness. So it’s completely natural, zero added sugar ;)