An Reccurent Event tracker including for software lifecycle

Hacker News

It's a project I'm working for some time, the starting idea was simple: I wanted to get simple notifications when reccurent events happen for example: I go to a site and I want to know when Windows (could be anything else) is launched, see the event in a calandar and get notified only for that every couple of years and nothing else. Of course as I started to work on it ideas started creeping in so by now it's far more than that. In the title I mentioned software lifecycle, you can already see this on https://endoflife.date/ but I also wanted to model this in a way that allows you to see them in a calendar besides other events. If you want to see what is tracked for software you can search for 'software' topic: https://www.beepwhen.com/event-series/topics Some feedback would be appreciated: 1. Is it is clear from the landing page what the app does? 2. If you think it's useful for you, if not why not , If it's useful, what stops you from using it I'm happy to answer any questions Thanks!

Visit product View on Hacker NewsSep 23, 2022

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, including · Missing: supports, reddit linkedin, podcasting

68%68% 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 HuntUnlikely to reach the leaderboard · Strong signals: model, using · Missing: mac, agents, macos

47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io, including · Missing: https docs, excited, just released

30%30% 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

27%27% 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

14%14% 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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