URL Roulette – redesigned site for discovering human-submitted links

Hacker News

URL Roulette allows you to submit a link and, in return, you are taken to a random site that someone else posted - no algorithm, no ranking, no AI‐generated content. It has been operating since 2017 and currently contains about 190K human‐submitted links in rotation. I reconstructed the whole project over the summer and it is now back online. I launched a weekly newsletter named The Vault that recaps unusual discoveries. I developed a bookmarklet named "The Boredom Button" that delivers a random link from any page with a single click. I would appreciate feedback on this. I am especially keen to hear from anyone who recalls the earlier version.

Visit product View on Hacker NewsSep 9, 2026

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2points

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Launch Intel predictions

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

73%73% 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.

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

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

42%42% 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

31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

28%28% 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

16%16% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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