I'm 17 and made a tool to help students study smarter

Hacker News

Hey HN! I'm Dris, a 17y/o solo founder. Over the past few weeks, I've been developing LIRA, a free Chrome extension that helps you take notes & get instant answers on any site. Instead of switching tabs or copying/pasting to ChatGPT, just select and right-click text, images, or links to save a note or ask LIRA anything. LIRA can instantly find accurate answers, summaries, and explanations, and automatically highlights correct answers. I made LIRA to help busy students like myself study smarter, not longer! That being said, LIRA is still a work in progress. There may be a few bugs & unfinished features, so feedback would be greatly appreciated. Thanks!

Visit product View on Hacker NewsNov 20, 2024

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

68%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, podcasting

59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: answers · Missing: mobile apps, ios, personal

54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

54%54% 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

45%45% 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

16%16% 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, smart · Missing: web3, crypto, cryptocurrency

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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