Discover high-quality articles,videos and more with human-curated lists

Hacker News

Hey everyone, Me and my friend were frustrated with garbage that we ran across on our search results and on the web. More than ever people are sharing articles, blog posts or videos on the web and parts of the web became a big garbage. So, we created Jooseph as a place where you can discover and share curated lists of high-quality articles, talks, podcasts and more. Also, we builded an extension to organize pile of tabs in your browsers. Basically you can create different collections in Jooseph to store or share your lists on Jooseph. (e.g. you can create a list about Best Golang Resources and make it private/public, you can add any link from your browser with the extension) I don’t know if it’s sounds good to you. We have shared here, a couple times. I am sorry if I am being spammy. But I wonder, would you be interested in using this kind of product and keeping closely in touch with us to solve your problem. (If you have this problem) You can take a look at from here: www.jooseph.com

Visit product View on Hacker NewsMay 23, 2020

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

68%68% 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, io · Missing: https docs, excited, just released

48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: video · 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

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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