Midnight.pub – Virtual Speakeasy

Hacker News

Midnight is a side-project I've been working on for the past year, but only released in alpha a month ago. It aims to be the web equivalent of your local pub: a place you can go to and talk about your day with strangers or friends. It's heavily inspired by write.as (for simplicy) and Roam (for bi-directional linking). My hope is that it fosters creative writing as well as typical pub discussions. You can read more about it and the concept on https://midnight.pub Here are some example of interesting stories written: https://midnight.pub/e/269435632215917061 https://midnight.pub/e/270853987488498184 https://midnight.pub/e/271216985664127501 Thanks for reading!

Visit product View on Hacker NewsJul 17, 2020

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

69%69% 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: month · Missing: mobile apps, ios, personal

63%63% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

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

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

41%41% 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

32%32% 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

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

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

Correct prediction on native model

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