@Brian Hennessey recently made an interesting discovery when his track Lifted landed on the high-reach Spotify editorial playlist "Deep Focus" (see https://www.instagram.com/p/DZ5ahDUCaiH/). The rumors about so-called "ghost artists" and the term "Perfect Fit Content" (PFC) used internally by Spotify were already uncovered some time ago in Liz Pelly's book Mood Machine. What I've been missing since then is quantifiable evidence about how common these artists actually are in major playlists. To shed some light on this, I've spent the last few days building a tool with Claude Code to identify the "ghosts". I'm currently cross-checking the results with Brian and wanted to share them with you. Full methodology and results are in the HTML file below. 👇🏼 If you know of other suspicious playlists you'd like me to run through the tool, or if you have tips and ideas on how to improve the detection methodology, I'd love to hear your feedback. 🎸

https://open.spotify.com/album/7qoVHP40UUdYcL1AIs9GoH?si=-BcEjTUjRY6hCU09hg1OQQ Friends! The illusive instrumental project is now alive and kicking! It's been sitting in the back seat of my mind as something I've wanted to do for a while, and now with the love and support of @Sebastian Jautschus and the rest of the community "Toe Beans" is now out in the world. My first song "Big Stretch" should be available wherever you listen to music, but i included the spotify link above. I massively enjoyed the whole process, and I'm determined to make my process as resistance free going forward, understanding more about recording, mixing, etc. I already have a ton more ideas I want to put out, so now I justneed to be disciplined on staying focused 😜 Thank you all so much for the support. You really are a bunch of wonderful human beings ♥️ 🐈🎸

Many new releases this May! Listing them below — apologies if I missed someone 🙂 - @Sebastian Jautschus : https://open.spotify.com/track/3S6A2DXqdsaUoPEngGNF75?si=aPcJDfPvSTG7fyq1-tVGyA - @Rebecca Mardal: https://open.spotify.com/album/33fiUPjr0y7Q8mx7SijUhW?si=mZCBxIAWRpWvAZTNbuLohw - @Slower Tempo: https://open.spotify.com/track/1tUToIeZGWwqSTLZGeAtxg?si=b-kVhdapSTmgbp8bFqEWdQ - @Brian Hennessey From Somewhere Quiet: https://open.spotify.com/track/79lEV0QpKMzAfcoxIJICh8?si=tiq6ji1MT-W7JQLRZzV-mQ - @Peter Monrad Friend From Work: https://open.spotify.com/track/7nMCXcQoC3owBO88Q8swky?si=8iG-ThyMRyetbTkJBcraLg - @Nathaniel Graham : https://open.spotify.com/track/2434qr9MVLrdOkgA5Vzyqg?si=ADDwbO7mS4Ges9NG6dJqwg - @Sebastian Henkelmann : https://open.spotify.com/album/36iBJUw5HiRK6y3WpZQziN?si=8q2ks12mSxyMAOB-vbQHzA - Not Enough Silence: https://open.spotify.com/track/6cMvnZciT4mV313kBY3o26?si=aB3wTS2TTkivrSvuKqC31A - Tides On Saturn: https://open.spotify.com/track/2XxOYFoIxTX48yJQ9cH6I5?si=Mcb0MKE5Tu2eJ8NRhBGRTg Also sharing my album From A Flood Of Words Only The Current Remains, which includes the single with @Rebecca Mardal plus 9 new tracks: https://open.spotify.com/album/1xPy6soMCJtMp1HmBe2KWD?si=Rx8Yh3xsSrayAPgUPH2vtw

Hey ya'll - I'm going to do it! I'm going to upload my first instrumental track under the artist name "Toe Beans" !!! BUT . . . . I'm getting myself into a bit of a pickle over making sure the song is as good as it can be for my first release - mix and master wise. I made some small adjustments and then attempted a go at mastering using stock plugins and a YouTube tutorial. I feel like I have no clue what I'm doing :P I want to get good enough to do everything myself and I appreciate that you have to keep doing it over and over to refine your process/style etc, but would really appreciate one more round of opinions before I release this bad boy into the world. Attached is a wav file so I hope it plays :P Basically, in short: Is this of enough quality to upload?

AI gets a lot of (justified) criticism in the music world right now, and watching what Suno and others are doing, I share those concerns. But I wanted to highlight a use case that's been genuinely helpful for me: data analytics. Over the course of one afternoon, I used Claude Code to build a set of dashboards with a tool called Streamlit, running locally on my machine and updated regularly with fresh data. No more wrestling with CSV exports (anyone who's dealt with DistroKid's royalty reports knows the pain 😅), just clean, visual overviews of everything that matters. And it goes beyond display. One question I'd always wondered about: how many songs should I actually put into Discovery Mode? Claude helped me work through that properly, with the data to back it up (see second screenshot). AI isn't replacing the music. But for the business side of things, the admin, the analysis, the stuff we'd rather not spend our creative energy on, it can be a serious time-saver. Happy to share more if anyone's curious. 🎸