We made a beautiful illustrated book on Bitcoin

Hacker News

Hey HN, For several years we tried to convince our relatives and friends of the importance of Bitcoin and its implications in their daily lives. We unfortunately failed to convince many of them :-) Having both of us had children recently, we came up with a last attempt at presenting Bitcoin. We decided to bring to life a book about Bitcoin that was as accessible as possible, featuring easy-to-understand concepts supported by beautiful illustrations. A book illustrated as one for children, explaining in the simplest possible terms the key ideas behind Bitcoin. We also wanted this book to be very quick to read for those that have little time available (or patience). This is how The Illustrated Guide to Bitcoin was born! We just released it today, it comes only in large physical format to appreciate at best its illustrations. We'll test it as a gift to our friends for this coming Xmas and we would really appreciate any feedback you might have! We would be super happy if it helps to orange pill your friends and family :-) Andrea & Ferdinando

Visit product View on Hacker NewsDec 15, 2023

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

84%84% 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: just released, ide, io · Missing: https docs, excited, exist

70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: physical, plain · Missing: mac, agents, macos

42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

27%27% 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

18%18% 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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