News, calm. Read your news once per day

Hacker News

Hi everyone, this is my first "Show HN", so i apologize in advance if I'm messing something up! I've recently released "News, calm", which is a way for you to follow any website and get an email once per day with the updates on each website (new articles, for example). It's an overhaul of something I released in September of 2018, called Focusd at the time. That product/service was only focused (ha!) on being a daily digest for RSS feeds, and the main thing I learned from customers using it in this period was that they didn't really care about the technology powering it, and that many websites people like to follow didn't have any RSS feeds. This concept is something I've been using for years (even before I converted it from a few lambda functions into an actual product) that has helped me tremendously to stop from spending too much time on news. To read HN I use the app's API and HN's API to get the top 3 stories per day, instead of everything new. It's OK to miss stuff. The URL is https://news.calm.sh/ and there's a free trial for 14 days without any limitation, so I'd appreciate hearing your thoughts on things I could improve on this. Thank you for your kindness and attention!

Visit product View on Hacker NewsApr 26, 2020

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

79%79% 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: new, email, using · Missing: mac, agents, macos

71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal

50%50% 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

31%31% 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

19%19% 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.

Incorrect prediction on native model

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