Mindcup
Indie HackersActive recall notes workspace with FSRS spaced repetition
Aspirants lose years to revision anxiety and information overload. As an ex-aspirant, I made Mindcup to automate the study process with active recall, converting intense daily effort into predictable retention.
Share cardActual performance
1followers
Did not reach leaderboard
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: notes · Missing: mac, agents, macos68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue28%28% 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, crypto17%17% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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The Visual Workspace – wireframes, flowcharts, sticky notes…
Indie Hackerscommitment-full-time