AI-native Metabolic Health App
Designing for future moms to regain the power of their own body
Context
I believe in learning by doing. I'm currently designing and building an AI-native metabolic health app that helps users understand glucose patterns and turn data into healthier, more sustainable habits.
As the sole designer and developer, I'm exploring how LLMs can make the experience more adaptive, personalized, and scalable — helping future moms and health-conscious users regain the power of their own body.
The problem
Future moms and health-conscious users lack accessible, intelligent tools to understand their own metabolic data. Existing apps present raw numbers without context — leaving users overwhelmed and disempowered rather than informed.
The opportunity
Continuous glucose monitoring (CGM) generates a rich stream of personal health data. The opportunity: use AI to translate that data into plain-language insights and personalized habit recommendations — making metabolic health intuitive, not intimidating.
My role
I am the sole designer and developer on this project. I'm responsible for the end-to-end experience: research, product strategy, UX design, visual design, and front-end development. This project is my deliberate investment in learning by doing — combining my design craft with hands-on engineering.
Design principles
Empowering, not alarming — Glucose data can spike anxiety. Every piece of information is framed around what a user can do, not just what is happening.
Adaptive by default — The experience learns from patterns over time. LLM-powered insights become more personalized as more data is available.
Honest about limitations — The app is clear about what it knows and doesn't know. It positions itself as a thought partner, not a medical authority.
Status
This project is actively in progress. Case study content and design artifacts will be shared here as milestones are reached.