PM AI Feature Launch
(2026 Edition)
Launching an AI feature safely means moving through five gated stages — internal dogfood, closed beta, limited public beta, gradual rollout with kill switches, then full launch — while enforcing eval thresholds at each stage, testing the kill switch before rollout, and monitoring hallucination and refusal rates, because AI edge cases scale with users in ways non-AI features rarely do.
By Naman Goyal · Product manager · Builder of PM Streak · Updated July 3, 2026
5 launch stages and 5 rules for AI feature launches.
Build AI Launch PM Skills — Free →5 Stages
Internal dogfood — at least 2 weeks before external
Closed beta with select power users
Limited public beta with feedback widget
Gradual rollout with kill switches
Full launch with marketing
5 Rules
Eval thresholds must be met at each stage
Kill switch tested before any rollout
Communicate uncertainty honestly in launch copy
Set up monitoring for hallucination and refusal rates
Plan for the 'weird tweet' — viral edge cases will happen
FAQ
Why do AI features fail at launch more often than non-AI features?
Because edge cases scale with users, and AI edge cases are weirder than UI edge cases. A non-AI feature might fail with bad data; an AI feature can fail in ways nobody anticipated. Gradual rollout, eval-driven gates, and kill switches turn would-be disasters into small incidents.
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