I built an on-device AI that asks why before you open your apps, here's what I learned

Meridian launches here on Tuesday. Before then I wanted to share some of what I figured out building it, because the hard problems weren't technical.

The technical problem was getting a local LLM running on Android without routing anything to the cloud. Solved that with llama.cpp compiled via NDK with a custom JNI bridge. Kairos runs entirely on your device.

The harder problem was behavioral. I don't think blockers work because they add friction without changing intent. You route around them in seconds or force yourself against your own volition in a war of attrition against yourself. Time trackers tend to not work because awareness without intervention just creates anxiety. Two extremes, neither felt like it addresses automaticity directly: The unconscious reach for the phone.

The intervention point I don't see anyone building at is the moment before the app opens. At least in a way that felt ethical to me. That's where Meridian lives.

One question. That's the whole product.

What I still haven't solved: Outside of direct feedback, how to measure whether it's actually working for users over time. That may just be a tradeoff of the selling feature of the app.

The r/QuantifiedSelf community pointed me toward tracking abandonment rate after the pause rather than the pause itself. That's squarely on the roadmap.

If you've thought about attention, HRV, behavioral loops, or on-device AI, I'd like to hear from you.