Captures the real requirements, hidden constraints, and the stakeholder's actual definition of done before a single line of code is written. Prevents the mid-build surprise.
In your own words, what does 'done' look like for this feature or project?
Describe what you'd see, click, or observe that would tell you it's working correctly.
What constraints exist that the ticket or brief doesn't capture?
Think about: performance requirements, compliance, integrations that must not break, legacy systems, other teams' dependencies.
How well-defined are the requirements going into this work right now?
Be honest — 'we think we know' and 'we definitely know' are very different.
What are the edge cases or failure modes you're most worried about?
What would a bad outcome look like? Who would notice first?
Is there anything about the current system that's important context for this work — something that isn't documented?
Decisions made years ago, workarounds, known fragile areas, historical reasons for odd behavior.
Who else has a stake in this that we haven't talked to yet?
Other teams, downstream systems, customers with specific workflows, compliance or legal.
What would you want a developer who's just picked up this ticket to know that they won't find in the spec?
The thing you'd tell them over Slack the day they start — the context that prevents a wrong turn.
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 7 questions · ~20 min session