From the late-night lo-fi sessions that got me through work to the high-energy anthems that fueled my morning workouts, these 634 songs represent the highs and lows of the past year. Looking at the raw list, a few patterns emerged:
Scrolling through the list reminded me of tracks I loved in March but forgot by October.
What does your music data say about you? If you haven't looked at your raw Spotify export yet, I highly recommend it. It's like a digital time capsule for your ears. Option 2: The "Curation & Playlisting" Blog Post
Why 634? It started as a simple text file of "must-hear" recommendations, but it grew into a massive curation project. My goal was to create a playlist that never gets old—a "shuffle-ready" universe of music that spans decades and moods. The Foundation: I started with my "All-Time Greats."
I spent hours ensuring the transitions were smooth, even on a list this size.
634 Spotify.txt Now
From the late-night lo-fi sessions that got me through work to the high-energy anthems that fueled my morning workouts, these 634 songs represent the highs and lows of the past year. Looking at the raw list, a few patterns emerged:
Scrolling through the list reminded me of tracks I loved in March but forgot by October. 634 SPOTIFY.txt
What does your music data say about you? If you haven't looked at your raw Spotify export yet, I highly recommend it. It's like a digital time capsule for your ears. Option 2: The "Curation & Playlisting" Blog Post From the late-night lo-fi sessions that got me
Why 634? It started as a simple text file of "must-hear" recommendations, but it grew into a massive curation project. My goal was to create a playlist that never gets old—a "shuffle-ready" universe of music that spans decades and moods. The Foundation: I started with my "All-Time Greats." If you haven't looked at your raw Spotify
I spent hours ensuring the transitions were smooth, even on a list this size.