Teach Us What You Love

Hacker News

When I was learning to play bass guitar, I had a discussion with my instructor about Bob Seger. My instructor scoffed, "He's a fat, aging hippie!" That was in 1979. So I have to hand it to my little brother, who, after 35 years of working at it, finally landed the keyboard role in a 'prog rock' band. They just did a CD and, for such a late bloom, it's impressive! So hey, all you prog rockers, what do you think? This one's called 'Teach Us What You Love': https://goo.gl/b3q1gL (opens in DropBox)

Visit product View on Hacker NewsApr 16, 2016

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

69%69% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

42%42% 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

40%40% predicted probability of success on Indie Hackers, 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

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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