Create forever running YouTube playlists

Hacker News

Hi HN, this is my first contribution on HN. I finally found some time again to create something new: https://streamforever.co lets you create forever running Youtube playlists that stream in sync with everyone who's watching. I use it almost every day to listen to NPR's Tiny Desk Concerts. The continuous "stream" has a feeling of a radio station. It got inspired by 247caseyneistat.com and i wanted to have something like that but for any Youtube playlist. This is work in progress, if you have any feedback, suggestions or feature requests, feel free to post.

Visit product View on Hacker NewsNov 13, 2018

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

73%73% 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.

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

51%51% 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 · Missing: mobile apps, ios, personal

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

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

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

24%24% 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

17%17% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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