It's hosted on a VPS, connected over Tailscale, and has a realtime TTS server (Piper).

The Pebble has built in transcription, so my app takes the transcript, hits the server endpoint with three possible paths:

1. Deterministic response

The server looks for certain triggers from the transcript like "Add task," "Complete task," "Set a timer," etc that will run a simple function on server and write / retrieve to a database, no LLM call needed. It then responds with the TTS output and the watch speaks. This path is nearly instant.

2. Fast response

If no trigger is found, then it hits a gpt5.6 Luna endpoint, which decides if it can answer the query itself, or if it needs to defer to the big brother model. If it can handle a query itself, it usually responds to simple questions in less than 8 seconds. It's also good about properly deferring, very close to 100% after a few weeks.

3. Deferred response

The VPS hosts a Hermes installation, and for more complicated tasks or for ongoing projects the Luna router sends it to the Hermes agent. This is typically quite slow, as you'd expect, but remarkably capable. I built the voice app to cache a few lines like "this will take some time" which will automatically trigger if the router indicates it's deferring, and then will respond with the full response from Hermes once it's finished (sometimes minutes later).

Pebble has a quiet mode, and my app will only display the text response if it's on, otherwise all responses are run through the TTS. Piper is so fast that this adds almost no time to the response.

In only a few weeks this has become the primary way I set up tasks, review and close them, set timers and reminders, log my weight, check in on the progress of projects I'm running on Hermes, and ask simple day to day AI questions.

Since Pebble is open source, AI tools are very good at building it, and it's trivially easy to set it up so that you can just ask the model to deploy it live. It's an awesome experience to tell it to change something, and two minutes later, that change is on your wrist.

Very fun project!

It's an attempt to get round the fact that various health apps and vendors pick and choose what they share or show from other sources.

I've been working on an AI Tutor or Primer that automatically generates Duolingo style curriculums. Planning to apply to YC after the next big feature release.

The current website is a rushed out MVP. It takes a significant amount of data science and prompt engineering to generate good courses, so it's taking me a bit longer to build the true vision.

I've been curious about ways in which politicians who are in the minority/out of power can still make progress on issues that matter to them.

- Stack enhacements

- Updates/upgrades

- Security audit

- Prometheus/Grafana monitoring and alerting

- Backups

Basically a sysadmin for my own local cloud.

Also hacking on something similar to YC's QM but designed for small non-profits to ease as much back office work as possible.