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We've seen hackathons where attendees build a SaaS business in a weekend. More than just Startup Weekend validation and a shitty MVP. A pretty-much complete SaaS product. It's a step change.

But this means the market for SaaS products is going to get hit hugely. If you can vibecode up a specific service for your specific requirement in a few days, why bother buying a SaaS product?

And, of course, if you can build a me-too SaaS product that imitates a successful competitor over a weekend, and then price it at 10% of their price, that's going to hit business models.

I think the SaaS startup gravy train is definitely over and done.

Personally, my sense is that there's a lot left to do in batteries + motors + LLMs. The drones in Ukraine could be smarter. Robot companions that can hold a conversation. Voice interfaces for robots generally [0]. Unfortunately, the people making all the batteries, motors, and increasingly the LLMs, are in China. So those of us stuck with idiot governments protecting their fossil-fuel donors are going to miss out on it.

[0] the sketch of two scots in a voice-controlled lift still resonates, though. There's probably still work to do here.

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The value in SaaS was never the code, it was the focus on the problem space, the execution, and the ops-included side.

AI makes code "free" as in "free puppy".


Right, there are dozens of open source versions of wikis/task trackers/CRMs/ERPs/whatevers. Just because you can vibecode your way to a bad version of a bunch of SaaS products shouldn't fundamentally change anything. Companies buy SaaS products to make running the thing someone else's problem. It's times like these where I wish we had a functional SEC; I really wonder how much market manipulation is going on.

Yeah, agreed, but it was at least part of the moat. Competitors can see the model, the approach to market, etc. They still had to code up a better product.

And part of the problem that the SaaS solves is that "I have this thing that I need to do. I can probably do it in software, but I don't know how. Can I buy that software?". Which is now becoming "Can I get an LLM to do it?" instead.


That’s where the “free as in puppy” comes in. It’s still a classic case of build vs buy, except building is now quicker than it used to be. You still have to ask, “suppose I did build it myself. Then what?”

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.


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.


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

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.


Can the output of the service be licensed? A bit like the AGPL, you're licensed to use/reuse/derive new works.

So if it's distributed outside of the license, that's subject to contractual penalties? I guess that's what all the "wrapper" SaaS businesses will do.

Read that report, it defined the issues and the boundaries well, for the current generation of AI tools. As they develop and expand, it's going to get interesting, especially if robotics/3d printing etc get involved.

If I use an Optimus Prime to help create art, similar to Andy Warhol's "factory", do I own the copyright on the completed work?

If a person uses AI to generate work that ends up being patentable, are patents also not available?


> The value in SaaS was never the code

I feel like a lot of people are about to learn this lesson for the first time. Except in some very niche areas the majority of the value was never the code. The SaaSs that everyone thinks will be replaced had much more than code if they were successful -integrations, contracts, expertise, reputation, etc…


Sometimes, but I think there are some SaaS products whose business model is really under threat. Look at PagerDuty. Their PE ratio is like 4.4. They have a lot of existing customers but virtually no pricing power now and I imagine getting new business for them is extremely difficult.

Canva is my go-to example - you can just get NanoBanana/whatever to generate and iterate on the image. Same for all those stock photo services. I used to use them a lot, now I just generate blog images

> AI makes code "free" as in "free puppy".

Exactly right


The biggest limiting factor is user acquisition. Just because you can build a competitor in a weekend doesn't mean you can easily acquire a user base. it's dam hard to get users even if your product is twice as good and your giving it away for free!

The implied risk isn't more SaaS competitors, it's that B2B SaaS consumers will just code up their own product instead of going with a SaaS vendor.

Started seeing even B2C folks just get the LLM to do it, or code up a quick solution that does most of it.



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