Devlog #10: Clearer plan results and more reliable training data
Plan summaries, progress history, reminders, and data checks now make training results easier to review and trust.
Development updates, guides, and announcements from the SkillTreq team.
RSS Feed ↗Plan summaries, progress history, reminders, and data checks now make training results easier to review and trust.
You can now set up libraries with less friction, choose from all activity groups, and trust that saved training data reflects what happened.
This update gives you more reliable metric input, clearer workout timing, and finer control over plans, deloads, and session changes.
AI-assisted plan import from spreadsheets, photo and video attachments on workouts, and a production deploy pipeline that builds, migrates and promotes in order.
Why we enforce deload weeks instead of hinting at them, why set logging moved to scroll pickers, and what four audit passes found before beta.
A visual overhaul of the library page, manual verification of all 29 tutorial libraries, and reliability fixes for active training sessions.
Phase 33 adds audio cues, wake lock handling, and a hands-free runtime so you can train without touching your phone.
A month of shipping: migrating the skill graph to canvas, wrapping the app in Capacitor for iOS, building a full equipment system, and launching the AI plan assistant.
Seven weeks of development: a full progress page, goal-based onboarding, expanded training session UX, and new libraries for tumbling, juggling, and weapon spinning.
A 201-commit sprint transformed SkillTreq from a skill tree prototype into a functional training app with active sessions, plan building, and a coach system.
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