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Infinite Hagakure

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Infinite Hagakure

Once upon a time I watched Jim Jarmusch's Ghost Dog and fell in love with the theme, aesthetic, and philosophy. The underpinning text is the Hagakure: The Book of the Samurai, with which the 14-year-old me became obsessed. After briefly reigniting my interest when reading a book by Yukio Mishima, I had a hazy idea of an infinite-scrolling Hagakure. Wherever you are in the world, you can open the page and jump right in at the same point as everybody else. It's not much, but it was an idea that formed and I'm pleased to have executed it.

Visit productView on Hacker NewsMay 22, 2025
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
78%78% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
65%65% 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 · Strong signals: open · 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: host · Missing: plus, platform, intuitive
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
26%26% 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
19%19% 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
13%13% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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