Mu
Mutter – follow ideas not people
Hacker NewsMutter – follow ideas not people
The Anti Social Network Here is our humble take on a new MVP much better Twitter where you: * discover links using swipes & AI * curate & share stream feed links * follow ideas not people :-) https://mutter.cards Check this out, and help us build this better, by sharing your suggestions on: feedback@psytech.ai
Share cardActual performance
11points
2comments
Made the leaderboard
Launch Intel predictions
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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive50%50% 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 released47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: new, using · Missing: mac, agents, macos46%46% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting21%21% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue17%17% 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, crypto3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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