Pagecord – Effortless blogging from your inbox

Hacker News

Hey HN I’ve been at a loose end for the past few days so I decided to build a thing. I’m largely devoid of original ideas so I built a (micro-) blogging app with a slight twist: you run it using email. All you need is an email account. No new tools to wrangle. No password to forget. Compose in your favourite email editor and send to a secret address. Pagecord does the rest. It's great for bloggy long-form writing, but it’s maybe even more fun for micro-blogging your thoughts as you would a Twitter feed (you can subscribe to people/blogs using RSS). I figured nobody would pay so it's entirely free (I do accept donations ). I put together a short video for the home page which shows it in action. There’s an FAQ at https://pagecord.com/faq and you can see my actual feed at https://pagecord.com/pagecord . That’s it. Just a bit of fun, but maybe some people will enjoy it. Let me know what you think and have a lovely day! -- Olly

Visit product View on Hacker NewsMar 28, 2024

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Actual performance

24points

14comments

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

88%88% 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, inbox, email · Missing: mac, agents, macos

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

55%55% 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: video · Missing: mobile apps, ios, personal

45%45% 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

30%30% 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

17%17% 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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