TIMELINE
ROLE
UX/UI Designer
TEAM
1 Product Manager
3 UX/UI Designers
DISCIPLINES
UX Research
Prototyping
OVERVIEW
solution
research
01
User Surveys
20 participants obtained through word of mouth and shared communities
02
User Interviews
5 participants across Zoom. Recruited through university channels
03
Secondary research
Collected through research papers on death and family dynamics
04
Usability Test & Critique
Many pivots after listening to feedback!





design







Conversation Guidance &
Digital Platform
80% of survey participants had already discussed death and legacy with their family — but wanted to go deeper on content and tone. And since 4 out of 5 interviewees lived apart from their families, we built a virtually accessible platform to guide those conversations from anywhere.

AI Guidance Chat
Survey responses and secondary research identified the most-discussed topics: advance care planning, financial planning, and memorial preferences. The guidance chat lets users explore these at their own pace before the real conversation happens.

AI Practice Chat
Participants P1, P2, and P3 wanted AI responses to feel more personalized and contextual — not generic. The practice chat generates scripts tailored to the user's family dynamics, birth order, and communication style.

Resource Hub
Testing showed mixed preferences — some users (P1, P2) were hesitant to rely on AI for sensitive topics and preferred independent research. The resource hub gives them that option, organized around the topics most requested in our surveys.

Saved Content
Meaningful conversations about death often happen in moments of crisis. The account tab lets users save chat histories and articles so they can come back to them when it matters most.
reflection
Get the AI principles down
I would dedicate more time to AI design principles to ensure the product followed best practices. With topics as sensitive as death, safety and privacy concerns surfaced across all testing methods. Our number one priority would be to address this to help with adoption.
Build a rapid prototype
We bounced around ideas for a prototype LM that could simulate a conversation, but due to time constraints we could not complete this. I believe building a functional conversational prototype earlier to test for edge cases would inform stronger design decisions.
