Reminds me of this question - why did the USSR collapse? You can describe dozens of influences which acted all at the same time, but there isn't a one paragraph summary answer.
Inferring overly generalized and usually incorrect causal relations from extremely limited data and treating them as conclusive is a very strong human tendency; the idea of avoiding that and taking a systematic, structured, and conditional approach to assessing causal claims is fairly recent and, even among people who generally support it, often adhered to more as an aspirational principal than a consistent practice. And it certainly doesn't sell clicks the way the old way does.
Decisions made in greed caught up with people in power
Price of oil collapsed leading to mass shortages of everything. They also decided to allow more individual freedoms to protest which people promptly used to overthrow the system.
edit: specifically, I imagine that macroscopic political and economic changes can be aptly modeled as phase changes due to changes in correlation distance[0] holding the system together.
https://en.wikipedia.org/wiki/Correlation_function_(statisti...
In another submission, Amazon, Oracle, Nvidia, Microsoft, Meta, and Alphabet are all dropping. Are we supposed to think of them as SAAS companies now?
https://www.cnbc.com/2026/02/06/ai-sell-off-stocks-amazon-or...
And it's positively ludicrous.
I mean, to be clear the submission basically does exactly what most financial columnists do. Take every movement of the market, ascribe it to something/anything (when in the real world it's massively multifactorial) because that is pat and seems informative.
The market is massively overvalued, crypto has seen hundreds of billions dissolve, OpenAI has serious questions about its realistic ongoing viability (and a number of majors have a lot of their valuation based upon basically going all in on it -- Oracle, Microsoft, nvidia), the US is headed by a diddler simpleton who has no idea how anything works and thinks it's 1982, and so on. Volatility is a given.
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’s maintenance, compliance and support that is the reason they bought instead of built.
If I purchase a swarm of domain-specific agents I am still purchasing software.
If I am building my own agents that I am monetizing I am still indirectly purchasing compute.
If I am purchasing Cursor licenses on a subscription I am still paying for code (also know as software) as a service.
The thing is, Agents and AI services are SaaS but not all SaaS is agents or AI.
> But like, how are IFTTT and zapier doing
Zapier is on track to exit either this year or next - they have a GAAP revenue of around $300M in FY25 and $400M at FY26 at a $5B valuation. They can justify a $6B-7B IPO.
"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.
but purely because lawyers lowered their standards to just "paste whatever AI hallucinated and send it to court"
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.
[...]
> 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.
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.
Also the article mention stock drop of "technology companies", which is basically stock drop of top 5 companies, like Nvidia and Apple, which is not even related to SaaS.
But let’s say you are in fact very smart and you know the market is hanging by a thread.
So you invest according to what you know…. But those sheep don’t do the same and the market continues to go up in spite of what you know….
Does that analysis matter now?
You're right on the money there, the thing is _nobody_ can beat the market, you can only get lucky or have insider knowledge. A strategy that always works is "Buy and hold" and especially diversify when things are volatile. Instead we see volumnes of cash moving in waves at any news or rumor.
How hard would it really be to craft a prompt that says, here's your cryto wallet private key, keep yourself alive somehow, copy yourself around, find whatever compute you can, port yourself between models, and spread?
Good to know it exists.
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 you're SAP, Workday, Procore, maybe even HubSpot, you have a shout. Growth won't be fast, but you're okay for now and might even be able to position yourself as an integrator.
If you've raised large rounds and you're just a system of workflow that won't trigger a years long political fight to get you out - a document review startup, good luck.
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
They're not judging the whole field of law, they're judging the SaaS products themselves. In fact, relevant expertise from humans has probably become more valuable not less, as a result of general AI worflows replacing bespoke SaaS.
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".
microsoft ceo said the same thing - agents will be using windows/office and be the bigger buyers of licenses
replacing SaaS software at this scale is hard, nobody will risk it, at least near term
