I really don't think the analysis here is that credible. People aren't leaving existing SaaS for AI agentic platforms like this article implies. Switching costs are too high even outside of tech, the problem runs deeper than that.
Most of these organizations are looking for customizations that B2B SaaS struggles to provide since they have to walk a line of catering to a market segment broadly then building customization for specific clients.
I've seen a huge surge in organizations investing in small software development teams to do internal builds for things that they just aren't getting from these tools. Technology is not the value center for these companies.
I work in healthcare, so my perspective is heavily contextualized by that, but I'm seeing providers (especially specialty providers) build internal engineering teams to create ancillary systems that sit on top of their EHR. They are doing this instead of buying similar modules that might be up sold by the EHR.
Anyway, I just feel like these market trends are deeper than what this article implies.
1. I was prepared my to roll my eyes, but I actually think the framing is correct. AI hasn't replaced legacy vendors yet, but companies are now in a position to at least assess whether "Cheap External Tool + AI" beats "Expensive Tool", which starts to compress margins for existing tooling.
2. A suspicious number of "It's not X, it's Y" in this piece.
I used to listen to the SaaStr podcast a few years ago. The way the host was always trying to prop up Jason Lemkin (the "author" of this article and the founder of SaaStr) gave me some weird cult of personality vibes. Add to that the fact that their annual SaaS conference (though they've been certain to "AI" to the marketing) generate some $10M in ticket sales suggests they may not be the most objective news source.
While AI was clearly what triggered this, I don't think AI is completely behind this fall. Many of these companies were overvalued and trading at quite high P/E ratios.
I really don't think the analysis here is that credible. People aren't leaving existing SaaS for AI agentic platforms like this article implies. Switching costs are too high even outside of tech, the problem runs deeper than that.
Most of these organizations are looking for customizations that B2B SaaS struggles to provide since they have to walk a line of catering to a market segment broadly then building customization for specific clients.
I've seen a huge surge in organizations investing in small software development teams to do internal builds for things that they just aren't getting from these tools. Technology is not the value center for these companies.
I work in healthcare, so my perspective is heavily contextualized by that, but I'm seeing providers (especially specialty providers) build internal engineering teams to create ancillary systems that sit on top of their EHR. They are doing this instead of buying similar modules that might be up sold by the EHR.
Anyway, I just feel like these market trends are deeper than what this article implies.
1. I was prepared my to roll my eyes, but I actually think the framing is correct. AI hasn't replaced legacy vendors yet, but companies are now in a position to at least assess whether "Cheap External Tool + AI" beats "Expensive Tool", which starts to compress margins for existing tooling.
2. A suspicious number of "It's not X, it's Y" in this piece.
I keep thinking about two very different cases wrt existing platforms:
1. My cousin who works for an enterprise real estate SaaS company. He said their main product has iirc 10-20,000 database tables.
2. Evernote users had famously little overlap in which features they used. Everyone use a slightly different subset of Evernote tools.
I wonder if you could create a 2x2 grid of these two scenarios to determine a SaaS tool's likelihood of being replaced with AI.
- Complex Data Model + High feature adoption: Low risk of AI
- Complex Data Model + Low feature adoption: Medium risk short term. High long term.
- Simple data model + High feature adoption: High long term risk risk, but limited ability to grow accouts
- Simple data + low feature adoption: Very high risk
You can smell the desperation in the air. From the LLM companies.
wanna hear what you have to say about this https://www.saastr.com/the-2026-saas-crash-its-not-what-you-...
I used to listen to the SaaStr podcast a few years ago. The way the host was always trying to prop up Jason Lemkin (the "author" of this article and the founder of SaaStr) gave me some weird cult of personality vibes. Add to that the fact that their annual SaaS conference (though they've been certain to "AI" to the marketing) generate some $10M in ticket sales suggests they may not be the most objective news source.
Reads like AI
While AI was clearly what triggered this, I don't think AI is completely behind this fall. Many of these companies were overvalued and trading at quite high P/E ratios.
Related:
AI is killing B2B SaaS
https://news.ycombinator.com/item?id=46888441
https://archive.ph/eA8vG