GetZen.news – A news app that only shows what affects you

Hacker News

Hey HN, I’ve been building GetZen.news, a minimalist news app that cuts out 99% of the noise and only shows you what actually affects your life based on your job, city, and interests. You can even ask it: “Why does this matter to me?” And it’ll explain why it showed you that article. It’s early just a waitlist for now but the idea is to replace doomscrolling with context-aware news you actually care about. Live here → https://getzen.news Would love feedback, questions, or concerns especially around trust, filtering logic, and how to avoid building another “black box” feed. Thanks for checking it out!

Visit product View on Hacker NewsMay 28, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, context, plain · Missing: mac, agents, macos

66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

42%42% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

39%39% 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

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

28%28% 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, 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

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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