Oh, so that's why my fancy 100% Merino wool sweaters don't stink like wet dog when wet, like regular vintage wool sweaters? I know there had to something different in the manufacturing process.

Everything is biodegradable, given enough time.

Isn't Coca Cola water reverse osmosis filtered?

The taste of local water should be irrelevant.

They don't do full reverse osmosis to the purest extent. There are still quite some minerals left. That's actually better for the end product

I can't speak for coke, but for bottled water, they often add minerals back in.

Honestly, the water is just a guess since the taste is different and the syrup comes directly from Coke. In other comments here, people mention the cans used but I’ve had Coke in glass from different countries taste different.

What kind of virtue signaling is this?

My memory works much better when I hear something than if I read it, when it comes to non technical stuff.

Apparently I'm ignorant about Tailscale, bacause your service description is exactly what I thought Tailscale was.

The main issue people have with Tailscale is that it's a centralised service that isn't self hostable. The Tailscale server manages authentication and keeping track of your devices IPs.

Your eventual connection is direct to your device, but all the management before that runs on Tailscales server.

Isn't this what headscale is for?

I'm afraid to ask, but because I've been very happy with Codex 5.2 CLI and I can't imagine Claude Code doing better, why is it Claude so loved around here?

Sure, I can spend $20 and figure it out, but I already pay $40/mo for two ChatGPT subs and that's enough to get me through a month.

Should I spend $20 to see for myself?

I'm a late comer to AI but I started using Gemini in June 2025.

Then in december I heard from my co-workers that they were liking Claude better than any other model, and from others online, so I bought myself some Claude for xmas. And I could clearly see that it was better, right away.

That's all I know, only one model to compare with, but the difference was definitely tangible.

It codes faster and with more abandon. For good results, mix Claude Code with Codex (preferably high or xhigh reasoning) for reviews.

Thanks. The reason for my hesitancy is that I've heard that the $20 sub isn't enough for anything meaningful.

If you spend only 20 on claude code you will not get far, it will lock you out after about hour of work for session usage limits

How much would you consider a good amount? I can't really afford more than 20$ myself, but perhaps there's a better more monetarily-optimal workflow.

The Claude models are among the most expensive. It's easy to spend 30 EUR+ a day when providing it with a lot of context, documentation. Ofc it can be argued that this money is worth it relative to salaries, but recently I've switched to kilocode myself after looking at different model pricings on openrouter https://openrouter.ai/models?order=pricing-high-to-low There's just no reason to throw money away.

There are plenty of free (and also cheap ones) models you can use with just openrouter or kilocode (inexpensive less-shitty Cursor basically, https://kilocode.ai).

With most things these free models are able to achieve great results and similarly to the expensive ones they need oversight and thorough code reviews. These days I'm barely paying anything for tokens monthly.

Its faster and the coding models before 5.2 for me did not work at all. Claude models have been reliable since 3.5

Not anymore. Meta didn't want competitors.

Mid band hearing is the last to go, unless there's lot of loud noise damage.

There's a things called 'hidden hearing loss' in which the ability to pause midband sounds specifically in complex/noisy situations degrades. This is missed by standard tests, which only look for ability to hear a given frequency in otherwise silent conditions.

https://www.audiology.org/consumers-and-patients/hearing-and...

This is freaking fantastic. However, as a community college instructor I would like to have this self-hosted on a computer in campus. Excluding the CLI niceties, etc., it shouldn't be to hard to get a similar setup with Docker et al, right? (not for production)

It's not possible to run real VMs with docker (though you can get something similar with qemu). VM isolation is also much stronger than docker's, and VMs tend to be much more secure.

But if you just need a shell then yes, you can make something similar with docker.

Memorization is learning. I don't think there's debate about that.

Whether memorization is useful on its own largely depends on the task.