Goodbye, Slopify

Spotify’s increasing use and promotion of low-quality or AI-generated tracks is seen by many as the latest stage in a broader “enshittification” of the service, alongside a cluttered UI, aggressive podcast and audiobook pushes, and perceived exploitation of musicians. Commenters describe how recommendation quality has deteriorated, playlists are quietly personalized or stuffed with “cheap” content, and useful APIs and third‑party clients have been shut down, reducing user control. In response, people are experimenting with alternatives such as Tidal, Qobuz, YouTube Music, Bandcamp, and self‑hosted libraries, often rediscovering older models of buying and curating their own music.

Tech naming and branding jokes

  • Many initially misread “Slopify” as mocking Shopify, not Spotify, leading into jokes about overused suffixes (-ify, -ly, -r, -ai) and domain scarcity (“getX.com”).
  • Nostalgia for the “Flickr/Tumblr” disemvoweled naming era; some mock current “SomethingAI” names as quickly-dating fads.

AI-generated music and Spotify’s incentives

  • Multiple comments allege Spotify promotes cheap “Perfect Fit Content,” including AI or low-paid session “slop,” to reduce royalty payouts; links shared to reporting on ghost/commissioned tracks and “fake artists.”
  • Some believe much of this is commissioned or third‑party, others think Spotify likely avoids generating it in-house but still benefits from it.
  • Users complain that unlabeled AI or ghost content pollutes mood/ambient playlists and undermines trust.

UI, product direction, and “enshittification”

  • Heavy criticism of the client: shifting layouts, accidental taps, constant A/B tests, degraded playlist/library management, and intrusive podcast/audiobook/course promotion.
  • Anger at removal or hobbling of third‑party APIs/clients (libspotify, DJ integrations), seen as a way to force use of the official, growth-optimized app.
  • Some recount quitting over autoplay bugs, forced DJ feature, and inability to hide sections or disable personalization.

Artist economics and platform power

  • Spotify is portrayed as fundamentally exploitative: low royalties, demonetizing under‑1,000‑stream tracks, bundling music with other media to push down music rates, and using platform-controlled playlists to steer listening.
  • Others counter that all major streamers pay similar pro‑rata rates and that mega‑stars structurally capture most revenue.

Discovery quality and algorithm changes

  • Many say Discover Weekly, Radios, and once-great genre/mood playlists have worsened or become hyper‑personalized “bubbles” that recycle old favorites and label-promoted tracks.
  • Complaints that shared playlists and radios now differ per user, undermining shared experiences and discovery.
  • A minority report that Spotify’s recommendations and DJ still work very well for them.

Alternatives and personal libraries

  • Suggested exits: Tidal, Qobuz, Deezer, Apple Music, YouTube Music, Pandora, Idagio, SoundCloud, Bandcamp, Hangout.fm, plus self‑hosted stacks (Beets + Navidrome/Jellyfin/Plex + local players).
  • Tools for migration and ownership: Soulseek, CDs/FLAC, Bandcamp purchases, playlist export tools, ListenBrainz, RateYourMusic/Sonemic, home servers, and refurbished/modern MP3 players.
  • Several describe deliberately returning to album-based listening and owning files to escape algorithmic slop.

Attitudes toward AI music itself

  • A sizable group “cannot stand” AI music and wants platform-level filters, watermarking, and clear labeling.
  • Others enjoy specific AI tracks, see it as just another production tool, or care only that music is good and non‑plagiarized.
  • Some foresee broader “AI slop” in podcasts and other media.

Why Spotify persists and disagreement on severity

  • One side sees Spotify as a “miracle” given cross‑platform access and huge catalogs; they mostly ignore recommendations and are content.
  • Critics argue licensing moats and label alliances block real competition, allowing long‑term “enshittification.”
  • Several note that the thread’s negativity may be skewed by HN’s technical, power‑user demographic.