A blog that deletes itself if you stop writing

Hacker News

I built Lapse because most of my blogs died quietly, abandoned after a few months. lapse.blog is a minimal blogging platform with one rule: if you don't post for 30 days, your blog is permanently deleted. No warnings, no recovery. How it works: - No signup. Your unique passphrase grants access to your blog. Same passphrase = same blog. (If two people pick the same one, they'll control the same blog by design) - The longer you post consistently, the longer it lives. Borrowing from social-media streaks, but for writing. If they can encourage you to Snapchat someone, surely we can encourage ourselves to write. - Markdown only. No images, no embeds. - RSS and Atom feeds included. - Forget your passphrase? Blog gets deleted. Stop posting? Blog gets deleted. - No ads, no tracking. The idea is that impermanence, hopefully, removes the pressure to be perfect, and the deadline offers an incentive to keep writing.

Visit product View on Hacker NewsJan 28, 2026

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3points

2comments

Did not reach leaderboard

Launch Intel predictions

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

68%68% 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 · Missing: mac, agents, macos

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

32%32% 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

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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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