Butt Mover - A butt triggered productivity and health improvement game

Hacker News

Productivity timers needed to be triggered manually before each task, Making it a chore by itself, Often leading to us not using them after a while and They don't take health into consideration. Health timers are intrusive, Even then they are not always accurate and They don't take productivity into consideration. Butt Mover addresses those problems by using a butt trigger for automatically starting the productivity timer when we sit on the chair before our workstation and a break timer which reminds us to take a walk automatically when we get up. Butt Mover also incentivizes its usage through a Game. When the health(tasks/breaks) reaches zero its game over. I've been iterating different forms of Butt Mover over past two years and released the web application earlier this year(After feedback from several HN users). Today I'm making the core application open-source as I've committed myself to make the Health & Education applications I build open-source. I hope you'd use Butt Mover for yourself and build Butt Trigger for others to improve productivity and health. Feedback and contributions to improve the project is appreciated.

Visit product View on Hacker NewsAug 4, 2022

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, tasks, using · Missing: mac, agents, macos

84%84% 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.

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

61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

47%47% 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

19%19% 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.

Incorrect prediction on native model

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