LearningStory – AI-Generated Tales for Bonding and Learning with Kids

Hacker News

Hi Hacker News, I'm excited to introduce LearningStory, an AI-powered platform that creates personalised stories for children based on a specified learning topic. I am a new dad to a 10 week old boy who was born 9 weeks early. When babies are born this early, they require extensive medical support, so he spent the first six weeks of his life in hospital. During this time, I found reading him stories to be a wonderful bonding experience. I especially loved stories that taught us something new. This got me thinking about all the things I'd like him to learn as he grows up and how amazing it would be to have storybooks that make learning fun and simple. This was the inspiration behind LearningStory. I'm new to software development, but I wanted to try to make and launch my idea quickly. I managed to build this in 4 weeks but it took some long days! I would really just love any feedback you guys can offer that might help with future products. Also any support on Product Hunt would be greatly appreciated: https://www.producthunt.com/posts/learningstory?embed=true&u... Thanks everyone, David

Visit product View on Hacker NewsJun 23, 2024

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3points

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Did not reach leaderboard

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

91%91% 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.

Hacker NewsStrong engagement from HN community · Strong signals: excited, hacker news, ide · Missing: https docs, just released, exist

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos

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

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

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · 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 · Strong signals: introduce · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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