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Premium Nature & Meditation Music Web App (my first solo project)

Hacker News

Premium Nature & Meditation Music Web App (my first solo project)

>>>>> TimeForZen.com <<<<< This took months to put together. Learning javascript, using the sound manager 2 api. Finding the perfect creative commons photos on flickr. It's such a ridiculously simple site (just a curated list of music) but I went through hell debugging and getting it to work. I learned an extreme amount. My advice to designers who can't code, keep it simple, just get it done don't worry about optimization, don't worry about a backend. Code everything manually if you have to. I've kept it simple out of necessity. I'm a designer, not a coder. I do front end html and css at most, so learning JavaScript was a big deal for me. Yes there's a million little things that can be added (like playlists, forums+comments, time tracker, accounts, etc... But I kept it simple so I could actually finish it. The javascript is probably 4x the size it should be because I (lol) did things the long & sure way rather than the optimized way, but hey. It's works. - I threw up a logo and the icons used in the session window. I'm not too crazy with the logo but it's alright. The icons bother me a LOT. They look unprofessional and need more work. - There's a glitch I'm still working on. The sound LOOPS over and over for tracks that are NOT suppose to have looped sound. - Works on Android and iPhones (glitch with absolute positioning and dom windows but sound will play). - Can anyone test this on an iPad? I tried to do it at BestBuy but they never have wireless internet set up.

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Indie HackersFits the IH revenue-focused audience · 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: using, code · Missing: mac, agents, macos
74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
56%56% 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: month, way · Missing: mobile apps, ios, personal
48%48% 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
44%44% 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
15%15% 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.

Incorrect prediction on native model

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