My

My new iPad App "Harken"

Hacker News

My new iPad App "Harken"

https://itunes.apple.com/app/id540251190 Why did I make Harken? Well, I use my iPad in my car connected to my car stereo and have it mounted on the dash. I was using the Apple built-in Music app but I found it quite difficult to use - it's quite hard to hit some of the buttons and choose tracks with my arm stretched right out, the text is too small, and it requires too many taps when all I want to do is choose an album to listen to. So I created Harken to be much easier to use in that environment but then I realised it would also be great if you have your iPad connected to a home hi-fi and like to see the album cover of what is currently playing from across the room. The same can be said if you have the iPad sitting on your desk while you work. The main selling points of the app are: - choose music based on album cover art, like you used to with a vinyl collection - see what's currently playing with a clean, easy to read interface - control playback with the absolute minimum number of gestures and large hit points for ease of use

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Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
88%88% 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: apple, new, using · Missing: mac, agents, macos
78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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
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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