Hi all, creator here :) - I launched Shepherd.com (
https://shepherd.com/) 3 years ago on Hacker News and have added a ton since then! Here is the original Show HN (
https://news.ycombinator.com/item?id=26871660).
I’ve interviewed 10,000+ authors & experts to get their 5 favorite reads around different topics, themes, and moods. And I’ve connected those so that you follow your curiosity around topics, authors, books, and more.
Try Art Kleiner’s favorite reads on understanding AI and its effect on people:
https://shepherd.com/best-books/understanding-ai-and-its-eff...
Under each book, you can click “What is this book about?” to explore different topics and genres that interest you. I am working on adding themes and other fun connections.
Or you can explore things like...
Places to explore if you like the book Sapiens:
https://shepherd.com/search/book/1504
S. B. Divya on her favorite realistic near-future science fiction:
https://shepherd.com/best-books/realistic-near-future-scienc...
Places to explore if you like hard sci-fi:
https://shepherd.com/search/shelf/12622
Places to explore if you like Stephen King:
https://shepherd.com/search/author/4826
Azby Brown’s favorite books on Japanese carpentry and construction:
https://shepherd.com/best-books/japanese-carpentry-and-const...
Malayna Evan’s favorite reads on badass women who left a mark on the ancient world:
https://shepherd.com/best-books/badass-women-who-left-a-mark...
Shepherd is bootstrapped, and I’ve got many reader features coming soon! I have a newsletter about building the project and early access to new features here:
https://forauthors.shepherd.com/newsletter-for-readers
What do we use to build this? Python, Django, Heroku, Postgre, Cloudflare, NLP/ML for Wikipedia topic IDs via Wikifier (https://wikifier.org), Nielsen’s book API database (publisher data + Library of Congress data), and Cloudinary.
My email is [email protected] if you want to share ideas or suggestions :)
Thanks, Ben
I’ve interviewed 10,000+ authors & experts to get their 5 favorite reads around different topics, themes, and moods. And I’ve connected those so that you follow your curiosity around topics, authors, books, and more.
Try Art Kleiner’s favorite reads on understanding AI and its effect on people: https://shepherd.com/best-books/understanding-ai-and-its-eff...
Under each book, you can click “What is this book about?” to explore different topics and genres that interest you. I am working on adding themes and other fun connections.
Or you can explore things like...
Places to explore if you like the book Sapiens: https://shepherd.com/search/book/1504
S. B. Divya on her favorite realistic near-future science fiction: https://shepherd.com/best-books/realistic-near-future-scienc...
Places to explore if you like hard sci-fi: https://shepherd.com/search/shelf/12622
Places to explore if you like Stephen King: https://shepherd.com/search/author/4826
Azby Brown’s favorite books on Japanese carpentry and construction: https://shepherd.com/best-books/japanese-carpentry-and-const...
Malayna Evan’s favorite reads on badass women who left a mark on the ancient world: https://shepherd.com/best-books/badass-women-who-left-a-mark...
Shepherd is bootstrapped, and I’ve got many reader features coming soon! I have a newsletter about building the project and early access to new features here: https://forauthors.shepherd.com/newsletter-for-readers
What do we use to build this? Python, Django, Heroku, Postgre, Cloudflare, NLP/ML for Wikipedia topic IDs via Wikifier (https://wikifier.org), Nielsen’s book API database (publisher data + Library of Congress data), and Cloudinary.
My email is [email protected] if you want to share ideas or suggestions :)
Thanks, Ben