Workoutmanager Plus — Development Roadmap

This roadmap structures development in clear phases. Manual input is treated as a platform adapter, not as a special case. Each phase builds on a stable and reusable data foundation.

Phase 0 — Canonical Data Engine (Foundation)

Goal: keep the core model stable and scalable: Identity → Representation → Occurrence → Execution, with governance on aliases and repository-based consistency.

• Remove mapping layer; workouts reference alias_id directly. [DONE]
• Alias n→1 canonical; snapshot principle implemented in workout_exercises. [DONE]
• Defaults on alias-level (equipment, variations). [DONE]
• Execution modes: Set-level vs Rep-detail mode with aggregation strategy. [DONE]
• Repository split: WorkoutRepository vs AliasRepository. [DONE]
• Audit logging v2 (append-only, JSON old/new values). [DONE]
• Time stored as seconds (`time`) in sets and reps; autosave support. [DONE]

Phase 1 — Manual Input as Adapter (Stabilisation)

Goal: complete and harden manual input so it behaves like any other platform adapter. Focus on consistency, autosave, and canonical storage.

• Refactor update_manual_workout_exercise.php to autosave-only behavior. [DONE]
• Universal workout model (platform-independent workout storage). [DONE]
• Workout editor UI: stable set/rep structure, rep-mode toggle, single reps-<set_id> container. [DONE]
• Mobile: rep notes modal using hidden autosave input (no backend change). [DONE]
• Finalize manual workout creation flow end-to-end (create workout → add exercises → sets/reps → complete). [IN WORK]
• Workout lifecycle handling: ensure status transitions and end-time behavior are consistent across UI + repository. [TODO]
• Improve validation/guardrails (negative values, empty fields, safe deletes) across all autosave endpoints. [TODO]
• Implement universal models for:
  • Body weight, height, and BMI [TODO]
  • BIA measurements [TODO]
  • Body measurements (circumferences) [TODO]
• Add manual entry UI for all body & measurement data using the universal models. [TODO]

Phase 2 — Speediance Deepening (Adapter + Governance)

Goal: import higher-resolution Speediance data and guarantee parity with manual entry. Speediance and manual should be interchangeable at the canonical model level.

• Import repetitions / per-set details from Speediance. [TODO]
• Align Speediance load/time fields with canonical set/rep schema. [TODO]
• Alias governance pipeline for Speediance imports (unverified → review → approve). [TODO]
• Validate parity: manual workout vs Speediance workout results (counts, totals, averages, durations). [TODO]

Phase 3 — Export, Reporting & Insight

Goal: move from data collection to reuse: export, reporting, and analysis layers. Advice is derived from normalized historical data.

• Export workouts to CSV/JSON (filter by date range, exercise, platform). [TODO]
• Define stable analytical views (aggregated sets/reps, volumes, durations). [TODO]
• Explore progress & trend reporting (R scripts / external pipeline). [TODO]
• Lay groundwork for future training advice and recommendations. [TODO]

Parallel / Supporting Tracks

These items can be developed alongside the main phases where appropriate.

• Email-based 2FA + “Trust this device for 24 hours” (split-token). [DONE]
• Device management page (list + revoke trusted devices). [TODO]
• Logout should optionally revoke current trusted device. [TODO]
• OTP rate limiting + attempt throttling. [TODO]
• Security headers review (CSP, HSTS, etc.). [TODO]
• Move menu structure to the database with multilingual support. [TODO]
• Implement multilingual support for the website. [TODO]
• Optimize layout for mobile and phone-sized screens (site-wide). [IN WORK]
• Workout templates. [TODO]
• Enable workout creation based on templates. [TODO]
• Redesign workout overview with left/right structure and total summary. [TODO]
• Analytics scalability options (materialized analytics, archiving strategy for >10M reps). [TODO]
• Canonical similarity scoring / governance confidence dashboard. [TODO]