There's something counterintuitive about building an AI product in the mental health and self-awareness space: if you're doing it right, your users should eventually need you less.
Most product teams optimize for stickiness. More sessions, more time in app, more daily returns. But at Murror, we've been wrestling with a different question what if the goal of our product is to help someone build enough self-understanding that they don't need to open the app as often?
In November 25, AI Context Flow was #1 Product of the Day and #1 Productivity Tool of the Week. It was surreal.
Since then, we have been building in public, together with this amazing community here.
You believed in this before it was polished. You gave us feedback when it was rough. You kept asking for more and that pushed us to build more, and we delivered more.
For the first year of building Murror, we optimized for the same metrics every other app optimizes for: daily active users, session length, screens per visit. The dashboard looked healthy. Usage was growing. We felt good about it.
But something was off. Our most engaged users were not our happiest users. People who spent the most time in the app were often the ones who left the harshest feedback. Meanwhile, users who opened the app twice a week for five minutes were writing us emails about how it changed how they handle difficult conversations.
I've been building my app for 8 months now, and i ended up having 5 repositories
nextjs app
databases
customer facing API
node-sdk that wraps the api
react-sdk, for both reusing shared component and customer facing components
So i thought, it's gonna be great if i create a mono repo with submodules. But it was terrible. I realized that turborepo does not like external packages, and as i tried to reuse my own customer facing libs, the DX became terrible. It was very time consuming to ship a feature. Even when i wanted to use Codex or Cursor 3, it was not able to show git diff properly, also i was not able to use Cursor's cloud agents properly to ship complex features.