I created a collection of useful websites

Hacker News

Hey all! Super excited to share this! If you're familiar with the r/InternetIsBeautiful sub-reddit, then you'll enjoy this. I built the website as a fun side project project over the weekend, and it re-imagines what r/internetisbeautiful would be if it was a newsletter. It's meant to be a completely free and community generated resource of the most interesting, useful and awesome websites from the depths of the internet. The list is tiny right now and I would love to hear your recommendations of websites that you think we should include. Hope you enjoy it, and would love to hear any feedback you might have. Quick question > Should we keep the "internetisbeautiful.co" domain or use a different one? It's meant to be a h/t and show of appreciation.

Visit product View on Hacker NewsJan 26, 2023

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

67%67% 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.

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

59%59% 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

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

47%47% 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

33%33% predicted probability of success on TrustMRR, 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.

Correct prediction on native model

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