Launch in stages, with a kill switch
Opening an AI feature to every user at once means discovering its flaws at the same time they do. This lesson teaches you to write a staged launch plan, with numeric thresholds for moving to the next stage and a way to shut everything off quickly, tested before the first user ever sees it.
Lesson objective
By the end of this lesson, you will be able to write the launch plan for an AI feature in stages (shadow, internal, canary, percentages), with quantified promotion criteria, an observation period and a kill switch tested before the first user.
Topics covered
- progressive rollout
- canary release
- feature flag
- kill switch
- AI launch
Where it fits
Launch without betting everything
How do you expose an AI feature to real users in stages, while being able to reconstruct every response?
Lessons in this module
- Launch in stages, with a kill switch (this lesson)
- Log and trace without exposing data
What you will learn in this module
This lesson is part of the course Ship and monitor an AI feature in production
- Design the staged launch of an AI feature (feature flag, shadow, canary, percentages) with quantified promotion criteria and a tested kill switch.
- Define what you log and trace for each model call, what you mask or exclude (personal data), how long you keep it, and with which tool.
Related courses
- AI & ProductAdvancedRegular practice: you already use the tools or work on this topic.
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- AI & ProductAdvancedRegular practice: you already use the tools or work on this topic.
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