vynl/ROADMAP.md

Vynl Feature Roadmap

Ordered by impact + ease of implementation.

Tier 1 — Big Wins, Easy to Build

1. "More Like This" Button

• Button on every recommendation card
• Uses that single song as seed for a new discovery
• Just pre-fills the Discover query with "find songs similar to [artist] - [title]"
• Effort: 30 min — frontend-only, no backend changes

2. "Why Do I Like This?" Reverse Analysis

• User pastes a song, AI explains what draws them to it
• Then finds more songs with those same qualities
• New mode on Discover page or standalone input
• Effort: 1 hour — new prompt template, reuse existing UI

3. Mood Scanner

• Simple mood sliders: happy/sad, energetic/chill
• Injects mood context into the recommendation prompt
• "I'm feeling chill and melancholy — find me music for that"
• Effort: 1-2 hours — UI sliders + prompt modification

4. Share Discoveries

• "Share" button generates a public link like deepcutsai.com/share/abc123
• Shows recommendations without requiring login
• Great for viral growth on social media
• Effort: 2-3 hours — new endpoint + public page

5. "Surprise Me" Mode

• One button, no input needed
• AI picks a random obscure angle from user's taste profile
• "You seem to like songs in D minor with fingerpicked guitar — here's a rabbit hole"
• Effort: 1-2 hours — new discovery mode, creative prompt

Tier 2 — Medium Effort, High Value

6. Playlist Generator

• Generate a full 20-30 song playlist around a theme
• "Road trip playlist", "Sunday morning cooking", "90s nostalgia"
• Save as a playlist in the app, export as text
• Effort: 3-4 hours — new endpoint, playlist creation, UI

7. Daily Digest Email

• Automated daily/weekly email with 5 personalized recommendations
• Brings users back without them having to open the app
• Requires Resend integration (already planned)
• Effort: 4-5 hours — Resend setup, email template, Celery scheduled task

8. Artist Deep Dive

• Click any artist name to get an AI card
• Shows: why they matter, influences, best album to start with, similar artists
• Modal or dedicated page
• Effort: 3-4 hours — new endpoint + UI component

9. Song Preview Embeds

• Inline YouTube Music player in recommendation cards
• Users can listen without leaving the app
• YouTube iframe embed with the video ID
• Effort: 2-3 hours — need to fetch YouTube video IDs (ytmusicapi), embed iframe

10. Music Timeline

• Visual timeline of when recommended/liked artists released music
• Shows patterns in user's taste ("you love 2008-2012 indie")
• Uses MusicBrainz release dates
• Effort: 4-5 hours — data fetching + timeline visualization

Tier 3 — Bigger Builds, Major Differentiators

11. Collaborative Discovery / Taste Compatibility

• Two users compare taste profiles
• Compatibility percentage score
• Shared "you'd both love this" recommendations
• Effort: 6-8 hours — friend system, profile comparison logic, shared rec generation

12. Vinyl Crate Simulator

• Gamified discovery: swipe through 50 random albums
• Tinder-style UI: swipe right to save, left to pass
• Rapid feedback builds taste profile faster
• Effort: 8-10 hours — swipe UI, album data source, feedback loop

13. Concert Finder

• After recommending an artist, check if they're touring nearby
• Link to tickets (Songkick API or Bandsintown API)
• Potential affiliate revenue
• Effort: 6-8 hours — external API integration, location input, UI

14. "Surprise Me" Advanced — Rabbit Holes

• Multi-step guided journey: "Start here → then try this → go deeper"
• Each step builds on the last, taking the user on a curated path
• Effort: 8-10 hours — multi-step UI, state management, chained prompts