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ReleaseJune 5, 2026

Review surfaces are more honest

Insights, Me, Settings, and workout labels now do a better job of separating source data, planned work, quick sessions, and account-related actions.

Shipped

  • Reshaped Insights around Overview, Performance, Body, and Tools.
  • Kept Insights focused on interpretation, while Me remains the source-data home for body, training profile, strength baselines, and equipment.
  • Moved visible equipment ownership into Me, while Settings stays focused on account, preferences, support, subscription, and app controls.
  • Tightened planned-work labels so Day Detail can distinguish pending, planned, unlogged, partial, and complete states more clearly.
  • Made planned-workout streak copy more explicit, so Quick Workout does not imply it preserves planned routine adherence.
  • Kept Quick Workout valid as real logged training while separating it from planned-work compliance.
  • Lightly polished local-first account and support surfaces so account creation stays available without blocking normal training value.

Why

Review surfaces are only useful when they are honest about the data underneath them.

An unplanned quick session can be valuable training, but it is not the same thing as completing a planned routine day. A lifter can finish a short conditioning session on Friday and still have an unlogged squat day from Thursday. Body and equipment information should live with the user profile, while Settings should stay focused on account, preferences, support, and admin choices.

This pass is about those boundaries. The app now explains more of what happened without making bigger claims than the local data supports.

Notes

  • Insights does not make predictive claims in this release.
  • Quick Workout can still count as a meaningful workout for first-run value, but planned adherence stays tied to planned routine work.
  • Account and subscription reminders remain light and contextual. The core training flow still works local-first.

Next

  • Keep review surfaces grounded in data the app can actually trust.
  • Add more interpretation only after the underlying logs and routines can support it cleanly.