Learntime – open-source AI-guided active recall app

Hacker News

Hi HN! I've built Learntime, an open source learning tool that combines un-prompted active recall with AI mentor support to help you retain information more effectively. Key features: - Un-prompted recall: Challenge yourself to explain entire topics without cues, actively reconstructing knowledge instead of relying on flashcards - AI mentor support: Dynamic hints help identify gaps and guide learning without giving away answers - Context-rich learning: Maintains relationships between concepts instead of isolated facts - Spaced repetition algorithm: Optimizes review intervals based on recall performance - Quick Quiz: Targets specifically what you've struggled with previously I built this because while there are many tools for acquiring information (YouTube, MOOCs, etc.), few focus on evidence-based retention techniques. GitHub: https://github.com/gerosullivan/learntime Try it: https://learntime.ai Happy to answer any questions!

Visit product View on Hacker NewsOct 22, 2024

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

75%75% 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: context, open, plain · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: answers, way · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: open source, ide, io · Missing: https docs, excited, just released

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

33%33% 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, revenue

15%15% 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.

Correct prediction on native model

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