The best practise for writing docs with LLMs in my opinion, which you have done, is to write as much as you can first then feed that into an LLM for context, and then work with the LLM to finalise it. Maybe half the time is spent writing and half the time is spent going back and forward polishing the doc.

Finally I think it’s important to give the LLM very clear writing guidelines based on your own writing style. I did this by feeding Claude around 20 of my handwritten docs and asked it to analyse my writing style and then add thy to its Claude.md. After a free round of iterations you can get great results!

For example I could never setup Traefik correctly because I just found it too complicated. Now I have Claude I finally got it setup just the way I want it - the ROI on my Claude subscription has been off the scale!

The obvious downside is that I might not really know what exactly I’m implementing and why. I do read all the explanations that Claude gives but it’s hard to retain this information. So there are pros and cons to relying on AI for this kind of stuff I suppose

My only concern about something like this is the WAF. My wife uses Trello. She would likely not use terminal. Also she only uses a phone so lack of mobile app or website is another blocker.

But it’s a cool app

There might be a future where you’ll have to pay more for an up to date model vs a legacy (out of date) model

So I wonder if there would ever be a middle ground between what artists would accept and what users would pay?

It’s essentially a pie that gets divided up amongst all artists by steam count. If your friend’s garage band are angry that they only get 0.001 cents per stream then they should be angry at Spotify listeners for streaming too much Taylor Swift!!!

Furthermore to pay the artists Spotify has to pay the labels and of course they take a giant cut. This trope of Spotify being an evil corporation is unfair

Of course the stock can rise again eventually.