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I built a simple habit tracker
Hacker NewsI built a simple habit tracker
Over the holidays, I built a simple habit tracker that lets you track any event's start and end time. In the process, I upgraded my personal homepage to Next.js 15, added Payload CMS and NextUI, and experimented with React Server Components and Actions. Check it out: https://mojica.de/tracker You can create new event types by entering activities in the top text field. Events are automatically started for new types.
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Did not reach leaderboard
Launch Intel predictions
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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting60%60% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released44%44% 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 · Missing: arr, mrr, revenue19%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, crypto1%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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