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Recipe Manager — Product Roadmap

Last Updated: 2026-03-23
Approach: Agent-driven incremental releases

Planning terminology: This file is the strategic Roadmap. Active coordinated delivery work belongs in .harness/*-execution-board.md (Execution Boards). Unscheduled ideas stay in Backlog sections.

Philosophy

Each release is shippable and usable — no partial features. Agents propose milestones, Paul approves, agents build autonomously.

MVP (v0.1) — "It Works!"

Goal: Anne and Elizabeth can create, organize, and cook from recipes
Timeline: 48-72 hours of agent work
Deliverables:

Core Features

  • ✅ Manual recipe entry — Form with title, ingredients (list), instructions (steps), source URL, notes
  • ✅ Recipe list view — Cards with title, description, tags
  • ✅ Recipe detail view — Full recipe with edit/delete buttons
  • ✅ Basic tagging — Add/remove tags (Dessert, Main Course, Quick, etc.)
  • ✅ Text search — Filter recipes by title or ingredients
  • ✅ Cook mode — Checklist UI for ingredients/steps, screen wake lock

Technical

  • ✅ SQLite database with schema migrations
  • ✅ REST API (Express + TypeScript)
  • ✅ React frontend (Vite + Tailwind)
  • ✅ Docker Compose deployment
  • ✅ Basic error handling + validation

Testing

  • ✅ Unit tests for API routes
  • ✅ Integration tests for database operations
  • ✅ Manual smoke test checklist

Documentation

  • ✅ README with setup instructions
  • ✅ API documentation (endpoint specs)
  • ✅ User guide (how to add/cook recipes)

Acceptance Criteria

  1. Paul can deploy locally and on paje.ca
  2. Anne can add a recipe manually
  3. Elizabeth can find the recipe and use cook mode
  4. No data loss after container restart

v1.0 — "Daily Driver"

Goal: Feature parity with CopyMeThat (minus community)
Timeline: 1-2 weeks (incremental agent work)
Deliverables:

Recipe Import

  • Browser extension (Chrome/Firefox) to scrape recipes from any site
    • Parse Schema.org Recipe microdata
    • Fallback heuristic parsing for non-standard sites
    • One-click import to local instance
  • Manual URL import — Paste URL, backend scrapes + parses

Enhanced Organization

  • Collections — Group recipes (Holiday, Meal Prep, Favorites)
  • Advanced search — Filter by tags, collections, cook time, servings
  • Sorting — By title, date added, last cooked, random

Cook Mode Improvements

  • Horizontal tablet view — Landscape-optimized layout
  • Serving size scaling — Auto-adjust ingredient quantities
  • Timer integration — Countdown timers for steps (optional)

Sharing & Export

  • Print styles — Minimal, card, full-page
  • Email recipe — Send as plain text or link
  • Export to JSON — Backup all recipes

Sync (Optional)

  • Multi-device sync — SQLite file sync via Syncthing or Dropbox
  • Conflict resolution — Last-write-wins with merge log

Testing

  • ✅ E2E tests for import + cook mode flows
  • ✅ Browser extension tested on top 10 recipe sites

Acceptance Criteria

  1. Anne can import recipes from her favorite sites in <10 seconds
  2. Elizabeth can scale a recipe for 8 people
  3. Paul can print a recipe for offline use
  4. All tests pass in CI

v2.0 — "AI-Enhanced"

Goal: Smart features that make recipe management effortless
Timeline: TBD (depends on AI integration complexity)
Deliverables:

AI Features

  • Ingredient substitutions — Suggest alternatives based on dietary preferences or availability
  • Meal planning — Generate weekly menus from recipe collection
  • Shopping list — Aggregate ingredients, de-duplicate, categorize by aisle
  • Recipe recommendations — "You haven't cooked this in 3 months, try it tonight!"
  • Nutrition estimates — Calorie/macro breakdown via USDA database

Fintrove Integration

  • Recipe cost tracking — Link ingredients to grocery prices
  • Budget-aware meal plans — Optimize for cost + nutrition + preferences

Advanced Features

  • Voice input — Add ingredients/steps via speech-to-text
  • OCR import — Scan recipe cards/cookbooks
  • Recipe rating & notes — Track favorites, add photos of results

Mobile App (Optional)

  • React Native or PWA for native mobile experience
  • Offline-first — Sync when online

Testing

  • ✅ AI feature accuracy benchmarks
  • ✅ Load testing (1000+ recipes, complex meal plans)

Acceptance Criteria

  1. AI suggests a valid substitution for missing ingredient
  2. Meal plan generation completes in <5 seconds
  3. Shopping list works offline
  4. Fintrove integration tracks recipe costs accurately

Future Ideas (Backlog)

  • Community recipes — Optional sharing with friends/family
  • Recipe version control — Track edits over time
  • Collaborative cooking — Multi-user cook mode (dinner party!)
  • Video tutorials — Embed YouTube/TikTok links
  • Equipment tracking — "Recipes you can make with Instant Pot"
  • Seasonal suggestions — "Fall comfort food recipes"

Agent Notes

How to Use This Roadmap

  1. Read PROJECT.md first for vision + constraints
  2. Pick the next uncompleted milestone (MVP → v1 → v2)
  3. Break milestone into tasks (1-4 hour chunks)
  4. Implement ONE task at a time — commit, test, document
  5. Update this roadmap when milestones complete

Decision Authority

  • Agents decide: Implementation details, libraries, file structure
  • Paul approves: Milestone completion, new features, major architecture changes

Communication

  • Progress updates: After each task completion (commit message + summary)
  • Blockers: If stuck >30 minutes, escalate to Paul with context
  • Proposals: New features or scope changes → document in PROJECT.md, ask Paul

Milestone Tracking

Milestone Status Started Completed Notes
MVP (v0.1) 📋 Planned — — Awaiting agent kickoff
v1.0 ⏳ Pending — — After MVP validation
v2.0 💡 Ideas — — AI integration research needed

This roadmap evolves as we learn. Agents: update it as you work. Paul: review and approve milestones.