Si

Simple, collaborative learning

Hacker News

Simple, collaborative learning

I'm a long time HN lurker, and wanted to show a side project that I recently started working on that I think has some merit. If you're an avid learner who is working on lots of different topics at any given time, as I know most HN folks are, you know that keeping track of what you are learning, the resources (books, tutorials, articles, courses, etc), and your progress along the way is difficult to do. LearnTribe solves this problem by providing a social way to organize and track your learning efforts. I'd especially appreciate some honest, but constructive criticism about the concept and implementation. Note that the site is lacking a real design treatment (mood, colors, logo, etc) and needs a look at UX. I'm hunting for a design partner to take the project to the next level.

Visit product View on Hacker NewsNov 13, 2012

Actual performance

1points

5comments

Did not reach leaderboard

Launch Intel predictions

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best fitHighest predicted score across all platforms for this description.

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AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

45%45% 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

14%14% 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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