People buy SAAS to offload the cognitive load of understanding the problem space, not just because it’s hard to write for loops.

But writing code probably is a cost. I think there will be an impact but I wonder if - these big companies keep selling to big companies because no one wants to hire a whole ass compliance team to ensure the business logic is consistently up to date.

But maybe there’s a whole lot of people caught up in edge cases that can be solved by a smaller team now? This I think is mostly what I hear about.

In summary, I suspect this is an overcorrection but there is some level of core concern here.

But like, how are IFTTT and zapier doing?

It is annoying to see a complex field as law being judge by stock prices of some SaaS products or w/e they are basing this on.

Could have at least gave it some effort and interviewed 2-3 people that use these kind of products but that would be too much work surely.

It is not surprising that people that slop like LLMs are so into LLMs

"Go away or I will replace you with a very small shell script" used to be BOFH lore, now it has become real. This is great.

That doesn't speak to the fundamentals, with which I only sort of agree. There are SaaS products that just grease inter-human interactions that would be hard to manage otherwise, and these are dead in the water. There are others that manage data human beings will always need to be able to understand, even if the AI is doing the work[1], which are much safer.

[1] Like bug trackers. We all love to hate Jira, but even if you have an army of Claudes doing your coding and testing for you someone somewhere needs to know what still needs to be fixed before shipment.

If the title said "WS just lost $285B because of 13 documents", people would have said "Why mention the documents? We get that people who move money around use documents".

In fact it should be opposite. Local utility software has higher chance of being replaced by AI as then you wouldn't worry about server and state and all the complexities of storage.

[...]

> For example, if you hold a company's accounting transaction data and related records, and expose it over MCP (or an old school API that can be wrapped into a CLI - which works better in my view), agents can use this with remarkable efficiency.

Sure why not wire all that transaction data directly into openclaw, what could go wrong?

Snark aside, it seems like there are two ways to go with a method like that if you want to keep the transaction data safe. The first is locally host your LLM(s) so the data stays on-prem. The second is to trust a third party to jump through all the legal and technical hoops to properly handle that very important, very private data. And if you're doing that, you're still doing SaaS. It's just a different provider.

I also think the SaaS has is doomed narrative does not work. There is a whole host of compliance, edge cases, reliability that I don’t you can simply bring in house because of AI assisted tools.

With that said I do think there are increasingly a whole host of more service based businesses where they are under threat. Thinking consultancy, legal, marketing or other similar roles. If you can use a leading model with these massive context windows to get 80% of the value for practically no time and no real cost compared to using a human where the quality will be higher might it might be a multi day engagement and easily 10-20k, you might start deferring some of the initial work to AI and only in certain cases then send it out to the human.