Write drum patterns, get randomized songs, then just share the URL

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I know mentioning Michael Seibel is almost cheating, but this week he demonstrated the "leaky pipes" concept to me. Not that I know the guy, but in one of his videos he says something on the lines of "If you are unsure if you app is ready to be launched, just launch it. It's like a house with leaky pipes, just open the main, grab your tools, and start fixing wherever water is leaking". So we did it, we launched drummy earlier this week on /r/InternetIsBeautiful and we got very close to 10k users in just one day! Survived the hug of death, learned a ton, and made changes all around. Still a ton of bugs to fix, features to be written, but at least now we can proudly present the "dummy drums challenges". Can you find the missing beats?

Visit product View on Hacker NewsNov 17, 2022

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

79%79% 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: user, open · Missing: mac, agents, macos

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

61%61% 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: video, users · Missing: mobile apps, ios, personal

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

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

35%35% 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

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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