I'm pretty sure Coursera or edX was using this same approach a while back — they'd make you type in a paragraph of text, then they'd use the timing information as a fingerprint or signature, to authenticate you as the actual student.
Someone here mentioned a whole ago that the labs deliberately haven't tried to train these characteristics out of their models, because leaving them in makes it easier to identify, and therefore exclude, LLM-generated text from their training corpus.
> I don’t care if you make an honest mistake. Hell, I don’t even care if you make a careless mistake, as long as you fix yourself. Everyone messes up - it’s how you act afterwards that matters.
You're not the one in control of their employment status and workplace reputation.
It looks like Slidev is designed for presentations about software development, judging from its feature set. Quarto is more general-purpose. (That's not to say Quarto can't support the same features, but currently it doesn't.)
I'm not affiliated with Slidev. I was just curious.
> It may be that like clothes, there's only so much need for software.
Clothing demand has increased greatly in the past decade due to fast fashion. Much of this clothing is designed to cost a few bucks, last a few wears, then get thrown out. It's an ecological disaster.
Maybe we'll see something similar happen with software — as production costs fall, trends will shift toward few-use throwaway software. I highly suspect this is already happening.
You would need to rerun the LLM, but you wouldn't necessarily need to rebuild the codebase from scratch.
You can provide the existing spec, the new spec, and the existing codebase all as context, then have the LLM modify the codebase according to the updates to the spec.