Posted by jnord 2 days ago
A couple of them mentioned that they plan to cancel subscriptions totaling more than $100k/year for the apps they will replace with that SaaS. According to them, they have many subscriptions they keep only because of one feature. Another issue is that their workflows become a real mess when they need to copy and paste data into multiple tabs. Custom-built internal tools seem like an obvious solution. Those who migrate to custom-built tools, however, will face the challenge of orchestrating their lifecycle and creating a consistent deployment workflow, but this is one of the challenges we are trying to solve at UI Bakery.
In my understanding, SaaS products that provide customers access to proprietary data are in a much better position than other SaaS platforms. HubSpot’s acquisition of Clearbit a couple of years ago now makes even more sense because it will help them retain some of their clients.
This practice predates even SaaS.
I read this article expecting to see a specific SaaS that was at risk, and the most I saw was "dashboards." (Which: dashboards frequently aggregate data, while the ongoing work of collection/maintenance/etc. is done by more complex applications.)
The thesis seems to be that companies can use coding agents to build one-off internal versions of SaaS apps like e.g. Workday or Salesforce or Slack or Jira or MixPanel or HubSpot. Which, if one could make such a thing for free and maintain it for free, why not?
Fortunately/unfortunately depending on where you sit, magical thinking isn't going to get Claude Code to build Workday, regardless of the quality of your AGENTS.md. Sometimes I wonder if the people who write these takes have spent any real time using Claude Code. It's good, but please be realistic.
They've outgrown the current (industry specific) products, arguably a long time ago. The discussions started like this:
1) Started building custom dashboards on top of data exports of said product with various AI tooling. 2) This was extremely successful, as a non developer "business" person could specify, build and iterate on the exact analytics. Painful to work with a developer on this as you need to quickly iterate once you see the data and realise where your thinking was wrong. Non developers also really struggle to explain this in a way that makes sense from a developers PoV. 3) ERP system at play wanted a renewal price which was a big increase, and API deprecation. This would require a lot of existing (pre "AI") integrations to be rewrote/redone. 4) Now building an internal replacement. They would not have even considered this before AI Agents.
FWIW this tool is not super complex, but it is extremely expensive (for what it does). It already has a load of limitations which are being worked round with various levels of horrible hacks.
There are a _lot_ of these kind of SaaS products about, for each industry. You never really hear about them.
Btw I use claude code nearly every day for many hours. Opus 4.5 has been a huge leap forward, I am blown away with how it can do 10-30 minute sessions without going wrong (Sonnet definitely needed constant babysitting). And the models/agent harnesses are only getting better. Claude Code isn't even a year old yet!
Overall, that story sounds more like the niche is not well-served by software and perhaps there is an opening for a competitor to serve them well. Or perhaps the attrition will make the incumbents improve.
As for Retool, I see the several waves of low/no-code products, the current one being LLMs, as repeated attempts to get non technical idea-guys to build their ideas. Where they all fail, and this is fundamental to the problem they're trying to solve, is that idea-guys' ideas crack when meeting reality. And neither Retool nor LLM fix that.
This is definitely the hardest nut to crack. I worked on a product a while ago that needed to track maintenance periods on equipment quite carefully and then use that to filter data to provide insights about how it was performing. The 'user story' was light on detail. As we got into it, there were tons of questions about how to deal with source data that was often inconsistent or patchy, time zones became an issue because much of the data we received wasn't matched correctly to their local time (customers fault not ours) and our ideas guy just couldn't deal with it - "make it work" - when ultimately they were business questions that needed answering, not just pure software tasks. AI is so sycophantic it'd just go off and write something.
The problem is, nobody knows how much and how fast AI will improve or how much it will cost if it does.
That uncertainty alone is very problematic and I think is being underestimated in terms of its impact on everything it can potentially touch.
For now though, I've seen a wall form in benchmarks like swe-rebench and swebench pro. Greenfield is expanding, but maintenance is still a problem.
I think AI needs to get much better at maintenance before serious companies can choose build over buy for anything but the most trivial apps.
When it comes to SaaS that's industry specific, I just don't see it'll be that much of a change any time soon. I've worked heavily in the engineering industry and the security requirements that get put upon anything are nuts. It is difficult to enter this market, ISO compliance is important, even being in the cloud is a barrier for some customers, and often the type that you have no choice but to contract with if you want to make a profit because of their outsized importance in the market.
When I speak to customers, they actually quite often have tried to build something themselves. Usually it's been an intern or grad trying to make their life easier. Often it's spreadsheet based, but some go as far as knocking up little Python web apps. In one company I interned in they had a shadow PHP app. They often have a small 'data science' team that has struggled to get access to the data they need. While they can often get something that does the barebones of the tasks, and can do it well, where they fall down is that they're vulnerable to security issues and can't navigate their internal company politics to get permission to host things in the cloud and make their life easy, plus they don't have the experience to know what's good practice. I don't see AI changing things that much in that.
The optimistic angle nobody's exploring: maybe 'eating SaaS' means we finally escape the subscription hellscape where every basic function costs $29/month. If an AI agent can stitch together free/cheap APIs instead of forcing you into Notion/Airtable/Whatever, that's not destruction—that's evolution.
This is inevitable, you can't rely on user licenses as a growth metric
Our customers ask for about AI features and it’s a constant struggle to explain to them that they just aren’t there yet.