I created a game to memorize the fretboard

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Hey guys I've been playing the guitar for many years but I felt like I had hit a wall and wasnt making progress. One of the things I realized was holding me back was unfamiliarity with the fretboard. I'd often find myself in situations like “Uhh…Where’s the C# here?” “Where’s the flat-3rd of this root on the 4th string?” “Sure would be nice to know the closest min7 triad shape to play over here..” I tried memorizing the fretboard the obvious way but it extreeemly boring for me. Being a developer, I decided to turn it into a game. I'd love for you guys to try it out and let me know what you think: It's at [www.fretboardfly.com]( https://www.fretboardfly.com ) I've only built the first module right now which is for note memorization but there's been enough interest that I'm planning on building more modules. Please let me know if you like it, what you'd change about it and what other modules you'd like to see in future. The stack is Vue 3/Nuxt 3/Firebase/Firestore/Tailwind deployed on Vercel. Happy to field questions on the tech side of things as well

Visit product View on Hacker NewsMay 26, 2023

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

77%77% 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.

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

66%66% 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 HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

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

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

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

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

34%34% 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

12%12% 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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