[marcus_holmes]

Yeah. So then you get your own product, tailor-made to your organisation, that you own (well, it's public domain because LLM-generated, but same same), and that you can change whenever you want without having to deal with a SaaS company's backlog. If you don't like something in it, you fire up Claude Code and get it changed.

There's also no danger of it being enshittified. Or of some twat of a product manager deciding to completely change the UI because they need to change something to prove their importance. Or of the product getting cancelled because it's not making enough money. Or of it getting sold to an evil corp who then sells your data to your competition. Or any of the other stupid shit we've seen SaaS companies pull over the past 20 years.

[otterley]

Respectfully, I think you’re only considering upsides and not considering downsides, opportunity costs, and ongoing maintenance costs. This is not what smart managers do. Plus, just because you can build something cheaper with an LLM doesn’t mean you can operate it more cheaply than a specialist can. Economies of scale haven’t been obviated by AI.

It’s useful to take an argument and take it to its logical extreme: I just don’t see every company in the world, large and small alike, building everything they depend on in-house, as though they were a prepper stocking up for Armageddon. That seems pretty fanciful on its face.

[marcus_holmes]

I hear that, and yeah, it's a possible future but I'm not sure it's the certain one.

The maintenance costs are kinda overrated: you fire up the LLM, point it at the code base and say "this needs fixing". I'd say that the maintenance costs of dealing with endless patches and fixes from a SaaS for features that you don't use is probably more onerous.

And generally we're talking about the situation where the SaaS customer is a domain expert in their area of expertise, but that isn't software development. They can use a system incredibly well, they just can't develop it. They have in-house IT folks to maintain their computers, networks, etc, and they're really just adding a couple of people to develop and maintain some applications via LLM to that team.

We're already seeing some of this, so it'll be interesting to see how far it goes.

[rswail]

Why is it public domain because it's LLM-generated?

[otterley]

As an attorney (and this is not legal advice), I would argue--and the U.S. Copyright Office has already stated--that machine-generated content is not copyrightable, because it's not a form of human creative expression. https://www.copyright.gov/ai/Copyright-and-Artificial-Intell... ("Copyright does not extend to purely AI-generated material, or material where there is insufficient human control over the expressive elements.")

That said, the inquiry doesn't there. What happens next after the content is generated matters. If human creativity is then applied to the output such that it transforms it into something the machine didn't generate itself, then the resulting product might be copyrightable. See Section F on page 24 of the Report.

Consider that a dictionary contains words that aren't copyrightable; but the selection of words an author select to write a novel constitutes a copyrightable work. It's just that in this case, the author is creatively constructing from much larger components than words.

Lots of questions then obviously follow, like how much and what kind of transformation needs to be applied. But I think this is probably where the law is headed.