Haven – Selfhost a private blog instead of using Facebook

Hacker News

Hi everyone, This project started as a way for me to share pictures of my then-newborn kid with close friends and family. I've always been privacy conscious and didn't really want to use Facebook or Instagram. The more I've worked on it, the more it feels like it could be a healthier way for people to interact on the internet--avoiding the polarizing, engagement-optimized algorithms that generate modern news feeds. I shared this project a few years ago: https://news.ycombinator.com/item?id=26013715 Since then (in addition to a lot of small things) I added a built-in feed reader. Haven already published private RSS feeds, now you can subscribe to those feeds along with any other RSS/Atom feed right in Haven. I'd love any feedback, thanks for taking a look!

Visit product View on Hacker NewsJul 31, 2025

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2points

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

87%87% 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.

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

74%74% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

70%70% 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

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% 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

11%11% 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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