Asakiri – Structured course creation platform for language teachers

Hacker News

Problem : Language teachers post valuable language lessons on YouTube or podcasts but they are not structured properly and don't contain notes. Solution : We give language teachers a platform where they can add their existing YouTube videos and add notes to them creating a structured course. We will also handle the interactivity by auto generating quizzes and other gamification material. The product demo is not connected to backend for now so you can't save a course but you can test out the interface and generate quizzes based on the content. I believe this will also give exposure to languages that are not the "popular" languages as anyone can create a course.

Visit product View on Hacker NewsNov 13, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: activity, notes · Missing: mac, agents, macos

67%67% 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, podcasting

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, interface · Missing: plus, intuitive, reviews

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, lua, existing · Missing: https docs, excited, just released

41%41% predicted probability of success on Hacker News, 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, revenue

23%23% 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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