Ai

Aika – a minimalist browser timer for 20-20-20 eye care and timeboxing

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Aika – a minimalist browser timer for 20-20-20 eye care and timeboxing

While spending long hours coding, I wanted a simple way to follow the 20-20-20 eye care rule (every 20 minutes, look 20 feet away for 20 seconds). I couldn’t find a browser-based timer that allowed recurring notifications with custom intervals, so I built Aika. It’s also been useful for timeboxing meetings and as a lightweight Pomodoro timer. - Runs in any browser - Free, no sign-up - Minimal by design Sharing in case anyone else needs something like this. Feedback is very welcome!

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
49%49% predicted probability of success on AppSumo, 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 · Strong signals: way · Missing: mobile apps, ios, personal
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: coding · Missing: mac, agents, macos
38%38% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
27%27% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: recurring · Missing: arr, mrr, revenue
24%24% 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.

Correct prediction on native model

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