Mobify.js, a client side adaptation framework for going mobile

Hacker News

Hey HN! We would love to hear your thoughts on our new client-side adaptation framework called Mobify.js. We've worked extremely hard on this product for a year and a half now, and we recently went open source with it. We use it internally to create mobile websites for our customers, and we would love for the rest of the world to use it too. Here is our first blog post on it: http://www.mobify.com/blog/introducing-mobify-js/. Once again, feedback would be awesome - go ahead and be brutally honest :)

Visit product View on Hacker NewsAug 11, 2012

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6points

2comments

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, open · Missing: mac, agents, macos

80%80% predicted probability of success on Product Hunt, 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: open source, ide, io · Missing: https docs, excited, just released

73%73% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

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

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

27%27% predicted probability of success on TrustMRR, 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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