Imagine turning your reading history into a treasure map. By feeding a list of your favorite books and movies to an AI assistant, you can uncover hidden patterns in what you love. From your subconscious attraction to unreliable narrators to your love for stories that begin at the end, you may be surprised by what an AI assistant can reveal.
Building a personal “taste atlas” helps you understand your reading self better. It can also surface blind spots in your cultural diet and point you toward unexplored literary territories you’re likely to love.
Why analyze your preferences? ⚡️
This isn’t just another recommendation engine. Netflix or Amazon may suggest what to watch or buy next based on viewing history, but a taste atlas goes much deeper.
It analyzes themes, narrative structures, and emotional resonance across media formats. It can reveal connections between novels you adore and foreign films you’ve never heard of, or help you articulate why certain stories stick with you while others don’t.
You can tune the atlas by adjusting the info and examples you give it. You can customize the analysis with your prompts, asking for particular kinds of observations or recommendations.
With AI’s help, you can map out your own universe of awesome. As you scout out gaps in your reading or movie watching, you can discover authors and films that expand your horizons.
Start by gathering your favorites 🤩
You need to provide an AI assistant with a list of at least 10-15 titles that resonate with you for meaningful insights; 30+ is better. Here are the fastest ways to gather them.
Physical books or DVDs: snap a photo of your bookshelf. AI can read the titles. Or write a list of titles on paper. AI assistants can read handwriting surprisingly well.
Digital readers: refer to your Kindle library (https://www.amazon.com/your-books), your “read” shelf on Goodreads (https://goodreads.com/), listen history on Audible, timeline on Libby (https://libbyapp.com/), or any doc or spreadsheet you maintain with your favorites.
Streaming: Apps like Likewise (https://likewise.com), Sofa (https://sofahq.com), Listy (https://listy.is), Listium (https://listium.com), Letterboxd (https://letterboxd.com), Trakt (https://trakt.tv), and Reelgood (https://reelgood.com) let you compile lists of favorites. You can use those collections to train your AI assistant.
Use your voice: If talking jogs your memory, use conversation mode in ChatGPT (https://chat.openai.com), Claude (https://claude.ai), Google’s Gemini (https://gemini.google.com), or Microsoft’s CoPilot (https://copilot.microsoft.com). Let the AI interview you about your favorite books or movies.
Scan award lists. If you can’t think of favorites, check a list of Oscar-winning movies (https://en.wikipedia.org/wiki/Academy...) or book awards (https://library.cumberland.edu/c.php?...) for reminders of what you’ve enjoyed.
Criteria: Consider titles you often revisit or recommend. Include recent favorites and older resonant ones. Give extra weight to those that provoked emotion, changed your perspective, or prompted action. Ideally, note not just the title but one or more aspects of a work that particularly resonated.
Prompt AI to analyze your list 🔎
Once you've compiled your list, use your preferred AI tool to uncover patterns in your literary tastes. Prompt the AI assistant for insights to advance your self-understanding. After that, ask it to help you discover more books/movies you'll love.
Start by writing a detailed prompt to elicit a thorough, subtle analysis of your taste in books or movies. Here’s an example you can adopt or adapt:
You are a perceptive literary critic and cultural analyst with deep knowledge of literature across genres and cultures. Carefully analyze the attached list of my favorite books for patterns. Think deeply about connections between titles and topics that might not be immediately apparent. Where you notice interesting patterns, explain your reasoning and cite specific examples.
Please analyze this list of my favorite books. Create a detailed literary taste profile that identifies:
Core Elements:
Primary themes and topics
Genre preferences and style patterns
Narrative approaches and structure choices
Character types and relationships
Tone and emotional range
»»»» Upload a file with your list or paste it.
Here’s a related prompt (https://lex.page/read/d1efb5af-338e-4... film.
Additional taste atlas prompts (https://lex.page/read/736c928f-05da-4...) to enrich your analysis.
Case study (https://lex.page/read/90905bf8-7f05-4...) of a taste atlas I created for my book group.
Which AI tool to use? 🎯
ChatGPT 4o worked well for me in importing Google Docs and PDFs with my favorites. Its analysis and recommendations were nuanced and helpful.
Limitation: Occasionally, it suggested authors who were already in my existing lists, despite...
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