Design a beta program that produces real learning: recruitment criteria, the feedback mechanisms that get used, and graduation criteria for GA.
Design a beta for: {{feature}} (what it does, what we're unsure about: {{uncertainties}}, candidate users available).
Design around the uncertainties — each one becomes a learning goal with a data source: recruitment (who, how many — enough for signal, few enough to support; the invitation that sets expectations: rough edges, feedback expected, direct access in return), the feedback machinery (a dedicated channel, the week-2 structured check-in call script, and instrumentation on the behaviours that answer our uncertainties — watching beats asking), the operating rhythm (triage cadence, what gets fixed during beta vs parked), and graduation criteria decided NOW (the usage/quality bar for GA, the kill criteria if it's not working, and the timebox). Include the beta-to-GA communication for participants — they became advocates or critics during this; end it deliberately.
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