It depends heavily on the domain. For B2B operations tooling, the real question isn't which stack to build with — it's which ecosystem your customers are already locked into.

If your target users live in Microsoft 365 + Azure AD, the integration advantages of the MS stack are hard to ignore regardless of technical preference. Same goes for teams deep in the Google Workspace or Atlassian ecosystem.

For our greenfield project we went with Kotlin/Spring + Next.js on the basis that most of our target customers use Jira+Confluence, so Atlassian ecosystem familiarity mattered more than stack choice itself.

The real issue isn't where you store notes — it's whether you find them when you actually need them.

I've gone through Notion, Confluence, and plain markdown. The pattern is always the same: I diligently save everything, then never look at it again because the moment I need it, I'm in a completely different context (a ticket, a chat, a meeting).

The "low friction = actually use it" point resonates. I've started thinking the answer isn't a better note-taking app, but surfacing the right information where the work happens, rather than making people go find it.

This is actually the truth, we all have tens or hundreds of priceless saved links. However, I claim that 90% are forgotten after a day or two, maybe that's actually something that small language models can fix ?

Spot on — the "90% forgotten" problem is real. I think the fix isn't really about the model size, though; it's about surfacing the right thing at the right moment. If the system can detect what you're working on and push relevant saved knowledge to you proactively, you don't need to remember what you saved in the first place. The hard part is getting the context matching precise enough to be helpful without being noisy.