I used to think that when I retired, I would spend my time writing short tutorials on topics I was interested in as a way to learn more about them myself. I've now been unemployed for three months, and while I've written some odds and ends, it's not nearly as fulfilling as I expected because I _know_ that most people aren't going to read a three-thousand word exposition of discrete event simulation: they're going to ask an LLM, and get something pseudo-personalized in return. 1/3
To be clear, I don't think this is inherently a bad thing: ChatGPT and Claude have helped me build https://github.com/gvwilson/asimpy and fix bugs in https://github.com/gvwilson/sim, and I believe I've learned more, and more quickly, from interacting with them than I would on my own. But they do make me feel a bit like a typesetter who suddenly finds the world is full of laser printers and WYSIWYG authoring tools. 2/3
GitHub - gvwilson/asimpy: Discrete event simulation in Python using async/await

Discrete event simulation in Python using async/await - gvwilson/asimpy

GitHub
I believe I can write a better explanation than an LLM, but (a) I can only write one, not a dozen or a hundred with slight variations to address specific learners' questions or desires, and (b) it takes me days to do somewhat better what an LLM can do in minutes. I believe I go off the rails less often than an LLM (though some of my former learners may disagree), but is what I produce better *enough* to outweigh the speed and personalization that LLMs offer? If not, what do I do instead? 3/3

@gvwilson

In many software applications, 99% uptime is unacceptable.

If you drive 100 km/h in the inner city, 99% of the time, no one will be harmed. This is not acceptable.

I think that in learning materials, 99% correctness is unacceptable.