A job board that helps you find impactful roles

Hacker News

Hi everyone! We wanted to make it easier for people to find high-impact roles across various fields, so we built a job board that highlights relevant opportunities. We’re a nonprofit, so this is completely free. When we say “high-impact”, we mean that we think these roles are relatively likely to lead to substantial positive change in the world. We recognize that there’s a lot of uncertainty regarding this, since although we look into the jobs that we list, there’s no way to be sure which ones will end up being impactful (not to mention that people have different definitions of “high” and “positive” impact). We also know that not everyone prioritizes this kind of impact, especially given how hard the job-search process can be. But, we still think there’s value in trying to aggregate these kinds of jobs, in order to help interested people find them.

Visit product View on Hacker NewsMay 16, 2024

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Actual performance

3points

1comments

Did not reach leaderboard

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

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

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

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

41%41% 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 released

39%39% 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: profit · Missing: arr, mrr, revenue

19%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, 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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