Meta Learning
Indie HackersA better way to learn - track, manage and learn how to learn
No-one ever taught me how to learn. Once I started looking into it, I discovered that there are objective principles and steps every learner should understand and apply. Meta helps learners learn.
Share cardActual performance
1followers
Did not reach leaderboard
Launch Intel predictions
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TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive15%15% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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