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Study Plannr – ChatGPT Powered Study Plans

Hacker News

Study Plannr – ChatGPT Powered Study Plans

Hi HN, I started off 20yrs ago as a programmer, then I became a computing teacher, now into edtech. With the launch of ChatGPT, I was captivated by it and decided to explore the use of it in development and education. Study Plannr generates personalized study plans with ChatGPT, based on subjects, topics, and assessment dates, helping K12 kids with their revision. I used NextJS and chatGPT 3.5 API for this app. I I host it on digitalocean. I developed this app because I have a K12 kid who needs alot of help in his studies. Usually, when his exams come, i try to create a study plan for him but it was quite challenging. Hoping this app can help. Do let me know any comments or feedback. Thanks!

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
82%82% 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.
TrustMRRFits verified-revenue profile · Strong signals: personal, education · Missing: mobile apps, ios, entrepreneurs
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: chatgpt · Missing: mac, agents, macos
53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
36%36% 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 released
29%29% 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
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
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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