I tried to build the first AI radio station

Hacker News

Hey HN, I grew up in Luxembourg & spent years near the old radio tower that blasted pirate radio across borders (unlicensed DIY broadcasts). I’ve always been into radio & wanted to hear what a 24/7 AI-generated “station” might sound like. It’s powered by ElevenLabs. GPT-5 gives each artist a little personality & generates music in their style. I built a simple algorithm that tracks upvotes/downvotes so good songs stick around & bad ones get dropped. Would love to keep working on this! I’m adding a host next & making the music generator better. Tech stack: * ElevenLabs * Inngest * Next.JS * Railway (a small HLS server)

Visit product View on Hacker NewsOct 24, 2025

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Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: host · Missing: plus, platform, intuitive

57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

18%18% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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