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Flow Timer - Time-boxing timer to stay focused

Hacker News

Flow Timer - Time-boxing timer to stay focused

Hello HN, I built a timer that can be split into multiple phases. Useful for time-boxing tasks and helping to stay focused. I often get distracted and spend ages on things I didn't originally intend to. A timer like this helps me stay focused and limit the time I spend getting distracted. It's simple without any bloat and fast to use. It's also open-source. The whole project is on GitHub: https://github.com/BryanHogan/flow-timer The site itself is on: https://timer.bryanhogan.com/

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
48%48% 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.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: tasks, open · Missing: mac, agents, macos
36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
32%32% 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
25%25% 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
17%17% 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.

Correct prediction on native model

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