Cadence – A Guitar Theory App

Hacker News

Hello HN, I just released this guitar theory and ear training mobile app which I've been working on for a bit more than a year on the side. The idea was to make something for the eternally "intermediate" guitarist (myself included). There are a lot of beginner apps which rely on learning songs, toolkits which give you a bunch of stuff with no explanation but not many in-between apps to actually learn and practice more generic and somewhat advanced stuff. The app contains short lessons, recaps and most importantly challenges (visual, audio and pure theory) along with a very complete library. The challenges are made for practicing, they will get increasingly harder and getting to the max score is supposed to be quite hard. The idea being that you have to repeat them regularly until your brain has integrated the info and it flows naturally rather than being a one time quick dopamine shot. It has no ads, a lifetime purchase option and you can use it without an account if you don't care about multi-device sync or backing up your progress. Android: https://play.google.com/store/apps/details?id=com.apizon.cad... iOS: https://apps.apple.com/us/app/cadence-guitar-theory/id674701...

Visit product View on Hacker NewsSep 20, 2025

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

95%95% 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: just released, ide, io · Missing: https docs, excited, exist

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.

TrustMRRFits verified-revenue profile · Strong signals: ios, apps, google · Missing: mobile apps, personal, entrepreneurs

61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: apple, google, apps · Missing: mac, agents, macos

49%49% 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

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto

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

Incorrect prediction on native model

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