filter and sort Who is Hiring jobs (or any other HN thread)

Hacker News

Lately I've been searching for a remote Android job and HN is a great place for this. I eventually got tired of loading the same thread day after day searching for anything new so I automated it. https://gist.github.com/delmatar/85a753092f60417cde7e This is quite generic. You can use it with any HN thread. It will find all first-level posts (replies don't count), filter and sort them by date. This way you only need to read what matters for you. Modifying the code for more complex queries should be trivial.

Visit product View on Hacker NewsMay 2, 2014

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Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

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

Product HuntUnlikely to reach the leaderboard · Strong signals: new, code · Missing: mac, agents, macos

45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

33%33% 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

21%21% 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.

Incorrect prediction on native model

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