PlaylistAI – Create Spotify and Apple Music Playlists with AI

Hacker News

Hey HN, I'm Brett and I'm an iOS developer. I made an app that makes you music playlists using AI in a few different ways. The main being AI prompts - you can enter something like "chill coding music, electronic" or "Music similar to the artist Bob Dylan" and it will generate a playlist for you. There are other ways to make playlists as well - using computer vision on images, sound recognition in videos, etc. Give it a try and share some playlists that you make. There's a demo video in my launch tweet here - https://twitter.com/brettunhandled/status/161317951121827840...

Visit product View on Hacker NewsJan 11, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: apple, computer, using · Missing: mac, agents, macos

93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios, video, way · Missing: mobile apps, personal, entrepreneurs

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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