Prompt-to-Publishable-Book

Hacker News

I'm thrilled to share something I've been working on for the past year. We built your dream tool for turning the idea you wished could be a book into a book - we call it Omniscience. It goes from a single prompt to a high-quality, cover-to-cover novel or non-fiction book. You can sample our non-fiction by reading Revolutionizing Life Design ( https://t.co/zfdBALBkNw ) and Unhinged Genius ( https://t.co/JVNXAJAqsE ) or our fiction by reading Omni Genesis. https://t.co/5WSQ3jsaA5 Plenty of other great works are available in the library, and you can follow our book prompting guide to generate your own masterpiece in our book writing interface. Prompt detail & complexity is king. You can take it from the words of one of our early evangelical customers: "Your tool has been a veritable boon for us, resembling a gift from Heaven." You'll get full hardcover and paperback cover art, the summary, full text & outline, and even recommendations for the Amazon keywords you should use. Everything you've written over the course of your life can be behind the book - uploading your data by syncing with Drive, choosing a website, or sending a folder or file from your computer and selecting it in the book writing interface will infuse the book with the knowledge you've chosen. From now until 24 hours after the launch, your first book will be free. Every book after that is paid. Happy reading & writing!! If you like the book generator, support us on product hunt today! https://t.co/GjQw60Vm5E

Visit product View on Hacker NewsSep 16, 2023

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

85%85% 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

63%63% 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: computer, single · Missing: mac, agents, macos

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

50%50% 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

31%31% 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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · 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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