The sleep-stage model is losing high-motion nights while the release window allows one change.
A gate adjustment preserves the new package while a rollback restores the prior behavior at the cost of recent improvements.
Who you’d be doing this for
“My sleep score showed up after lunch again, and I’d already changed my workout plans.”
Nari Morita · Frequent app member
She uses daily sleep and readiness insights to decide whether to train before work.
What is at stake
High-motion confidence coverage fell from 95% to 86% after a firmware rollout. You have to weigh a targeted gate change against losing recent model improvements in a rollback.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- high-motion recovery vs low-motion stability
- model correction vs app-side continuity
- fast deployment vs reproducible validation
Why Ōura
Sleep insights in the mobile app depend on reliable interpretation of motion and physiological signals across real nights.
Written with these in mind
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This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.