I brought GitHub to the Apple Watch: Why?

Hacker News

I'm looking for feedback on the beta of my new app called WatchGit which brings GitHub to your Apple Watch. You can get the beta from Apple TestFlight(https://testflight.apple.com/join/ipzDjzSy). You can create issues, comment, add and remove labels, assign and more. https://watchgit.com/ Hard-press the watch screen in the app to create an issue directly in the support repo. Bugs, enhancement requests etc. are all welcome. WHY? If you don’t always have your phone with you, for example when out running or walking, and you have a brilliant idea for a new feature you can simple raise your wrist and use Siri to create an issue in a repository from your cellular Apple Watch. You can also easily triage issues, assign issues, like issues, etc. without pulling out your phone. If you always have your phone to hand then it isn’t for you, but if you like to leave it behind sometimes then it may be something to try out.

Visit product View on Hacker NewsJun 12, 2020

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

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

45%45% 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.

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

29%29% 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.

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