[abakker]

Great to see your name here, Zack. I think the problem with low-code is that its a catch all that spans between primarily data-storage-and-use work (Airtable, quick base, Filemaker, etc), the primarily app-alternative platforms (retool, Mendix, etc, and the ETL tools.

To me, AI changes the inflection points of build vs buy a bit for app platforms, but not as much for the other two. Ultimately, AI becomes a huge consumer of the data coming from impromptu databases, and becomes useful when it connects to other platforms (I think this is why there is so much excitement around n8n, but also why Salesforce bought informatica).

Maybe low-code as a category dies, but just because it is easier for LLMs to produce working code, doesn't make me any more willing to set up a runtime, environment, or other details of actually getting that code to run. I think there's still a big opportunity to make running the code nice and easy, and that opportunity gets bigger if the barriers to writing code come down.

[zackliscio]

Great point, and I agree the catch-all nature of the category feels overly broad. At our company, we've felt this shift most clearly on the app-building side so far but I'm curious to see how the low-code data applications fare as context windows grow and the core LLM providers improve their collaboration tools, governance, and improve the UX of on demand app creation. And nice to see you, too!