Capture what a departing long-term volunteer knows about the program they served in before that knowledge leaves with them.
What program or role were you volunteering in, and for how long?
Give us context on the scope of your involvement.
What does this program actually do day-to-day that isn't obvious from the outside?
The informal routines, workarounds, and practical knowledge that keep things running.
Who are the key people — staff, volunteers, or community members — that the next volunteer should build a relationship with?
Include why each person matters, not just their name.
What challenges in this program have never been fully resolved?
Recurring problems, tensions, or gaps that the organization is still working through.
What advice would you give to the volunteer taking your place?
What do they need to know to be effective that isn't written down anywhere?
Why are you stepping back, and would you consider volunteering again in the future?
This helps us understand what motivates and sustains volunteers over time.
After each completed session, Mayetik generates a structured AI summary. Here's an example of the output format — the actual content reflects each respondent's answers.
The respondent's answers highlighted three recurring themes — each supported by specific examples drawn from their experience. The summary captures what was said, not what was expected.
Two responses stood out as unusually detailed and pointed to an area worth following up on. The full text of each answer is preserved below the summary.
Based on the patterns in this session, the AI identified three concrete actions for the project team to consider. These are drawn directly from the respondent's own suggestions.
Generated from 6 questions · ~3 min session