vrotaru

It is a personal project, which the author uses for some other personal projects.

Clade - a programming editor with elastic tabstobs and Smalltalk like navigation

Maybe, there is more. Looks to me like an illustration of the "It is a quiet life" meme

There is a (Bertrand Russell?) quote about axiomatic approach having the same advantages as theft compared to honest work.

I'm not sure exactly why this came to mind. Vibes?

It looks like we all enjoyed "Security through obscurity", where obscurity was referring to existing vulnerabilities.

And also, that this is over.

Since Goose, compile to C, I guess the answer is yes, but..

With the but part being the really interesting one.

Good observation. Also there is some funny stuff with what the book say referenced appendices do and what those actually explain

At the end of chapter 30 we have:

   Next: Appendix A — OCaml Setup and Tooling

But the after the chapter 30, follows the chapter 31, and Appendix A is called

    Appendix A: Ocaml Quick Reference

And the link is a dead link.

This has strong vibes of "Do this and you will get rid of back pain" followed by the video of some crazy acrobatic stunt.

Congrats, BTW.

Here is my experience.

Claude did generated a rather good template for what I needed. It did not compile at first but I copy-pasted the errors and it fixed them.

Not all was good, though. It used literal bullets instead of `-` required for lists, but on whole the experience was positive.

It had taken me less time to fix the template than it would been taken to write it from scratch.

Something which Claude was good at. I throw him a crude ASCII "art" representation of what I want and get the right Typst code back.

Sorry for harping on it, but I think this clearly reflects the difference between 2 approaches to storing knowledge, lossy but humongous, and lossless but limited.

LLMs - Lossy highly compressed knowledge which when prompted "hallucinates" facts. LLMs hallucinations are simply how the stored information is retrieved.

Memory (human in this case) - Extremely limited, but almost always correct.

Just an observation. No morals.

There is a podman-compose which works almost as drop-in replacement.

Almost because most common commands work, but I have not check all.

And almost, because for some docker-compose.yaml which you downloaded/LLM generated you may need to prepend `docker.io/` to the image name

That is a good questions and I guess we have good progress since Plato whose definition was - A man is a featherless biped.

But I think we still do not know.

To some degree *all* LLM's answers are made up facts. For stuff that is abundantly present in training data those are almost always correct. For topics which are not common knowledge (allow for a great variability) you should always check.

I've started to think of LLM's as a form lossy compression of available knowledge which when prompted produces "facts".

Well, not exactly convince. I was curious what will happen.

If you are curious it was a question about the behavior of Kafka producer interceptors when an exception is thrown.

But I agree that it is hard to resist the temptation to treat LLM's as a pear.

You should always check. I've seen LLM's being wrong (and obstinate) on topics which are one step separated from common knowledge.

I had to post the source code to win the dispute, so to speak.