SinglePage – Quickly and anonymously publish a page to the web

Hacker News

Creating a basic webpage has become way too complicated and expensive. Often there are those times when you just want to share your thoughts with the world but don't want the overhead and complexities that come with maintaining a website. Sometimes, you have an interesting thought piece, an education article, or just a quick and simple bio page that doesn't need the heavy hand of a WordPress blog or Medium post. That's where Single Page comes in. Publish a single page instantly to the web with no fuss. I was laid off three weeks ago from Twitter and I decided to work through a couple of my projects and this was one of them. I've tried blogs over the years, Medium didn't feel right but yet I wanted to quickly post pages online and couldn't find an easy way to do it. So I created it. Feedback appreciated!

Visit product View on Hacker NewsNov 29, 2022

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Actual performance

175points

132comments

Made the leaderboard

Launch Intel predictions

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

69%69% 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 HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

52%52% 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

43%43% 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 · Strong signals: way, education · Missing: mobile apps, ios, personal

41%41% 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

15%15% 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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