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StartupWeekend pitch - open source music player and radio

Hacker News

StartupWeekend pitch - open source music player and radio

Being a coder and desk jockey like many of us, I spend a lot of time plugged into my music collection or the "radio". The problem is that I don't trust iTunes after losing my history in a system crash. The cloud should solve that and also be available online, but comes with unfortunate restrictions. My plan for this weekend is to build an open source, web based, music player, and social radio. This may sound like a tall order, but we will have a working demo in two days and all of our work will happen on github for everyone to see. (https://github.com/comster/disco) If you're a javascript hacker or frontend designer who's interested in building a better music app and social radio, join team disco.js! [end pitch] [For example of the radio feature, see turntable.fm .] The technology stack is all javascript. Node.js, Mongodb, and Backbone.js are the weapons of choice. Obviously my goal is to meet and learn from hackers at the event, but this is also a chance for me to shamelessly plug my open source platform as a service framework that I'm putting together (https://github.com/comster/house). It's just a bunch of open source components put together to provide a basic app development platform. The goal is to minimize your dev time on the server, so that you can focus on the application experience. This weekend gives me a chance to prove it can support a complex app like disco.js, and to get feedback from other developers and hopefully improve the architecture. I'm looking for hacker feedback! Thanks in advance :)

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Actual performance

3points
1comments
Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
77%77% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: code, open · Missing: mac, agents, macos
66%66% predicted probability of success on Product Hunt, 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.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
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
13%13% 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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