Hmm, suppose Claude Code can make a prototype.

But who's going to deploy it, make backups, integrate authentication, review security?..

Now, perhaps, it would be nice to have some kind of a ERP framework which would host AI-generated apps and connect them to each other. Is there anything like that?

My understanding is that agents are:

1) helping to saturate traditional SaaS because code is being commoditized / the effort to build is dropping significantly.

2) defining an adjacent sub-category of SaaS: "Service-as-a-Software" where the SaaS provides _outcomes_ instead of _tools_; this couldn't really exist at scale before recently.

I’ve been saying this for months:

https://efitz-thoughts.blogspot.com/2025/08/the-effect-of-ll...

When you say agents, do you mean the workflow runners that can call APIs and automate the workflow steps?

Automation is not new. What's new is the capabilities of the models that can be assigned with some of the workflow steps. If these steps were served by SaaS companies so far, they will still serve it. Maybe they make it much cheaper and use a model themselves.

This is borderline schizophrenia. Firstly, nobody replaces something that works with something that might or might not work.

Secondly, the way this person describes "agents" is not rooted in reality:

>Agents don't leave. And with a well thought through AGENTS.md file, they can explain the codebase to anyone in the future.

>What's going to be difficult to predict is how quickly agents can move up the value chain. I'm assuming that agents can't manage complex database clusters - but I'm not sure that's going to be the case for much longer.

What in the world. And of course he's selling a course. This is the same business as those people sitting in Dubai selling $6000 options trading courses to anyone who believes their bullshit. The grifter economy around AI is in full swing like it was around blockchain/crypto in 2017-2020.

The ffmpeg wrapper use case is interesting. Reusing some core software for speed and reliability but to get better usability by leveraging LLMs seems like the sweet spot for SaaS use cases. A lot of these CRM products are basically wrappers around DBs and sheets like core products with terrible UI. The new breed will solve the UI ease of use issues.

>SaaS valuations are built on two key assumptions: fast customer growth and high NRR (often exceeding 100%).

They are also on the basis of high gross margins of 80-90%. What happens to margins when you start including token variable costs?

The real question isn’t whether we’ll run out of SaaS customers, it’s whether we’ll run out of new problems that can be solved by the current set of tools. I doubt it, it’d be a historical first in the modern era. But the solutions may move closer to the companies with the problems. More in-house, fewer intermediaries.

The only SaaS that AI has eaten for us is Retool. It wasn't the cost (we were paying < $200 per month). Retool has become more clunky to use vs. writing code with AI to solve the problems we used Retool for.

I think the biggest impact will be on SaaS products from startups and side projects. People will think, "I can build something myself with the help of AI, so why should I pay to try your unfinished product?" The barrier to entry has become higher, requiring a more complete product.