How can families manage Type 1 diabetes more holistically while strengthening parent-child communication day to day?
Project
Codi
Healthcare
Codi is a collaborative mobile app for families navigating Type 1 diabetes. It helps children and parents communicate clearly through a research-backed, user-centered experience.
I built a shared decision system that helps families capture daily health events, detect conflicts, and resolve them clearly.
All of this is powered by Firebase behind the scenes—every log entry and every mismatch resolution is stored securely in the cloud. That means families can always access their data, and the app can instantly sync updates between parents and kids. Firebase made it super easy to keep everyone on the same page, whether they're logging meals or working through a disagreement about what really happened!
Overview
Role
UX Engineer & Full-Stack Mobile Developer
Timeline
November 2025 - Present
Holistic care: Built a guided chatbot logging flow that made health entries easier for children and parents.
Execution: Led frontend delivery and shipped production ready child and parent experiences from research insights.
Communication impact: Improved family data alignment through mismatch detection and resolution workflows.
Stack / Tools
Development
Design & Research
Demo
Loading video...
Highlights (My Key Contributions)
- Chatbot logging UX: Built the conversational logging UI for both children and parents so entries feel guided instead of form heavy.
- Cross-domain health logging: Implemented structured capture flows for food, activity, mood, symptoms, sleep, and insulin updates.
- Adaptive prompts: Added fallback branches like 'I don't remember time' and 'I'm unsure about carbs' to reduce drop off and incomplete logs.
- Usuals plus new entry flow: Implemented fast path selection for recurring behaviors while preserving full custom logging when needed.
- Mismatch detection logic: Built type specific comparison rules across child and parent logs (time windows, carb deltas, intensity and quality mismatches, symptom and mood differences).
- Escalation design: Implemented urgent routing for symptom and negative mood cases so parent visibility is immediate when risk is higher.
- Resolution workflow: Built a decision flow where child and parent choose the correct log, submit rationale, notify each other, and converge on final data.
- Confirmation layer: Added keep, edit, and discard handling so data quality improves through explicit reconciliation.
- Feature delivery: Built core React Native communication and care coordination flows.
- UX translation: Turned usability findings into reusable components and clearer interactions.
- Cross functional ownership: Partnered with design and research to iterate quickly.
- Alignment: Ran weekly cross functional reviews across supervisors, design, engineering, and research.
- Decision quality: Aligned engineering with UX goals to reduce rework and ship faster.
- Adaptability: Expanded frontend ownership while maintaining delivery momentum.
Outcome
- Scalability: Established a production ready frontend foundation for continued feature delivery.
- Process impact: Tightened feedback loops between research, UX, and engineering.
- Business readiness: Positioned Codi for pilot testing with clearer validation milestones.
- Learning: Improved how I translate research into product decisions and implementation scope.
Next steps
- Release: Ship the next deployment ready candidate.
- Validation: Run pilot testing with live CGM workflows.
- Prioritization: Convert pilot findings into the next roadmap.