Tennessee Caregiver Coalition (TCC) connects caregivers with volunteers to provide respite care through bi-monthly community support events.
The existing platform created unnecessary friction for caregivers, volunteers, and staff.
A unified registration and event management platform tailored to three user groups.
As Product Manager, I led a 10-member UX team through a 16-week project, translating research and stakeholder needs into MVP priorities and coordinating design, testing, and handoff while utilizing AI-assisted workflows.
Our initial audit suggested registration and navigation needed the most attention.
User research revealed a different set of priorities across caregivers and volunteers.
Across 10 interviews and usability testing sessions, we found that some workflows worked better for the people actually using them than our audit-based assumptions.
Registration wasn't universally difficult.
“I think the current registration process is pretty straightforward and easy to navigate.”
The real problems lay in places we weren't even looking, like in the repeated, detailed intake forms caregivers had to deal with.
Repeated intake was exhausting for caregivers.
“No parent likes to fill these forms out... We just get tired of it.”
Auditing the platform showed that volunteer training materials were buried behind several clicks, making a mandatory task harder to achieve. In fact, of 93 currently registered volunteers, 46 weren't marked as trained.
TCC staff explained that volunteers arriving unprepared create difficulties, particularly at Parents' Night Out events where volunteers work directly with children.
We used Claude with Figma MCP to explore concepts quickly, but the drafts still needed human judgment. One AI-suggested staff table seemed organized on the surface, but buried key actions like opening participant profiles.
We made training progress visible in 3 ways: top-level reminder, progress bar, and organized status sections.
Our final prototype separated workflows clearly so we could focus on what each user needed most, bringing relief to caregivers, clarity to volunteers, and control to staff.
We carefully annotated the high-fidelity Figma prototype and documented important UX decisions, client context, and product specifications to support TCC's development phase.
This was my first larger project using AI-assisted prototyping, and it was pretty cool to see how fast we could churn out and test our ideas. However, I quickly realized AI didn't give us a “skip iteration” button, just a new way to get into the work!
I was responsible for both delivering something great to our client and being a pillar for my team. By communicating openly, setting clear expectations, and leading with the same willingness to contribute that I hoped to see from others, I built a team culture where people felt comfortable asking for help and supporting each other.
Our audit gave us plenty of things to redesign, but talking to actual users challenged some of those assumptions. I learned that knowing when to leave a good thing alone is just as important as knowing what to change.