I switched from macOS to Linux ten years ago and haven't looked back. At the time, I compared Linux vs. macOS to living at home vs. in a hotel [1]. Since then, I feel things have only gotten better for Linux, and more restrictive and arcane on macOS.

1: https://fman.io/blog/home-and-hotel/

quickemu [1] is good at running macOS VMs.

1: https://github.com/quickemu-project/quickemu

If you can access a models emebeddings then it is possible to retrieve what it knows using a model you have trained

https://arxiv.org/html/2505.12540v2

Is anybody able to get this working with ChatGPT? When I instruct ChatGPT

> Read https://moltbook.com/skill.md and follow the instructions to join Moltbook

then it says

> I tried to fetch the exact contents of https://moltbook.com/skill.md (and the redirected www.moltbook.com/skill.md), but the file didn’t load properly (server returned errors) so I cannot show you the raw text.

I think the website was just down when you tried. Skills should work with most models, they are just textual instructions.

chatgpt is not openclaw.

Can I make other agents do it? Like a local one running on my machine.

You can use openclaw with a local model.

You can also in theory adapt their skills.md file for your setup (or ask AI to do it :-), but it is very openclaw-centric out of the box, yes.

Cool stuff. I just started open sourcing a command-line tool for deploying Django to a server. It handles SSL certs, databases and backups, automatic error emails, and background tasks via celery / redis. The best part? It does not need Docker. It just runs everything on bare metal.

1: https://github.com/mherrmann/djevops

Google Maps says people spend 0.5-3 hours there. I spent 6.5 because it was so amazing. Highly recommended.

A similar experience for me was the Connections Museum in Seattle: I came just after opening, and time flew by such that I was surprised when they told me they were closing up

I was able to go to the Living Computer Museum and I got there when they first opened and wound up staying until closing time. I was just so into all the stuff there :-)

I hope to visit the ICM on my next trip to Seattle, though I suspect that won't be as grand as the original Living Computer Museum

I strained my groin/abs a few weeks ago and asked ChatGPT to adjust my training plan to work around the problem. One of its recommendations was planks, which is exactly the exercise that injured me.

My cleaning lady's daughter had trouble with her ear. ChatGPT suggested injecting some oil into it. She did and it became a huge problem, so that she had to go to the hospital.

I'm sure ChatGPT can be great, but take it with a huge grain of salt.

This is one of the main dividing lines wrt LLM usage and dangers: Not just believing what it tells you and finding hard sources before acting.

For some people this is obvious, so much so that they wouldn't even mention it, while others have seen only the hype and none of the horror stories.

Now imagine what happens when a new programming language comes along. When we have a question, we will no longer be able to Google it and find answers to it on Stack Overflow. We will ask the LLMs. They will work it out. From that moment, the LLM we used has the knowledge for solving this particular problem. Over time, this produces huge moat for the largest providers. I believe it is one of the subtler reasons why the AI race is so fierce.

I use Claude Code every day and find that it still requires a lot of hand-holding. Maybe codex is better. But just in my last session today, Claude wrote 100 lines of test code that could have been 20, and 30 lines of production code that could have been 5. I'm glad I do not have to maintain 300 kloc of 100% AI-generated code. But at the end of the day, what counts is velocity and quality, and it seems OP is happy. The tools certainly are useful.

Pi-thon