Remote working resources

Hacker News

Hey Hackernews! My names Olly (a Designer from the UK). I’ve been a long time lurker on Hackernews but now I finally have something to share with the community. Along with my friend Oliver (Developer, Sweden/Japan) we have been working on Remotewise.io. It’s a new resource and learning platform dedicated to remote work. We’ve both been working remotely for most of our careers. Over this time remote work has been gaining huge momentum as a viable and desirable way to work and we believe it’s the future. We’ve been working on this during our evenings and weekends in between our full-time remote roles, so we’re really excited to be putting it out for you guys. We’d really appreciate any feedback as I’m sure many of you are remote workers yourselves or thinking about going that route. You can check it out here: https://remotewise.io So, why did we create Remotewise.io? We noticed it was often tricky and time consuming to find quality and relevant content about remote work and the companies which champion it. We wanted to create a focused, discoverable and beautifully curated list of resources so that you can learn from the leaders in the industry, what it takes to work as a highly effective remote team and how to nurture a healthy remote culture. We see the site as a learning and discovery platform that in the process helps you find the best company fit for you, hopefully taking the pain out of searching for that perfect remote role. We’re launching a weekly newsletter too so if you’re into it sign up and receive the latest updates. We’ll also be bringing you founding stories and leadership interviews in the coming weeks and months. This is just the start of our journey, there’s loads more to come. We’d love to hear your feedback as it’s really early days for us and we’re excited about where we could take it. You can also reach us at hello@remotewise.io or tweet us @remotewise. Massive thanks, Olly & Oliver

Visit product View on Hacker NewsFeb 14, 2019

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nativeThis product was originally launched on this platform.

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57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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29%29% 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

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.

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