An app to improve touch typing by typing out whole books

Hacker News

Hey everyone, Ive built an app where you can practive touch typing by typing out whole books. I am a developer who recently learnt touch typing, I needed to practice typing to improve my muscle memory. Used monkeytype and keybr for a while and I got fed up by typing random words. So i looked for platforms where I can type out books, because I am anyways typing, might as well read something meaningful while I am at it. I found some platforms, but i didnt like the experience, as since I am a backend web developer myself, I decided to build one which I can use and polish my frontend skills. Please do try it out, ive spent months building it, any feedback on how to improve the app is really appreciated, and I hope you enjoy the app :)

Visit product View on Hacker NewsSep 30, 2024

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3points

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

77%77% 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

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

52%52% 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 · Strong signals: platform · Missing: plus, intuitive, reviews

37%37% 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

18%18% 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.

Incorrect prediction on native model

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