The track pipeline was the proof of concept. Download a preview, run the analysis, write thirteen numbers back to Salesforce. Repeat for every track in the catalog. The playlist pipeline is a different problem entirely. To score a submitted track against a playlist, I need to know what the playlist actually sounds like — not just its name and follower
The last post ended with thirteen audio features computed from a 30-second preview clip. Energy. Danceability. Valence. Acousticness. Tempo. Key. Mode. And six more. That’s a lot. Too many for the Scoring Engine to reason about directly, in fact. If the goal is to decide whether a submitted track fits a playlist, I can’t ask the Scoring Engine to reason
In the last post, I mentioned that Spotify deprecated their Audio Features API – the endpoint that used to return energy, danceability, valence, and a dozen other musical characteristics for any track. It just disappeared. No replacement. No warning. No timeline. That was the moment this project stopped being a submission tracker and started becoming something I hadn’t planned to
After the intro post, a few people asked the same question: why Salesforce? Fair question. Salesforce is enterprise CRM software. It costs money, has a steep learning curve, and comes with the kind of bureaucratic reputation that makes developers wince. It is not, on the surface, an obvious choice for a solo musician trying to get their songs on playlists.
There’s a saying in investing: it takes money to make money. Music has its own version of that problem – it takes listeners to get listeners. If you’re an independent artist on Spotify, you already know this. I’m a software developer and a musician. When I ran into this wall, I did what any developer would do: I tried to build my way out of it.