Literary Roots Notebook

“Which authors feel like home?”

This notebook captures the feel, themes, and craft of storytellers you love. It’s the foundation of your Voice and often reveals your Themes.

Notebook Name: Literary Roots – [Author/Titles]


Source Checklist

Goal: Capture the feel, themes, and craft of 1–2 “literary ancestors,” not everything ever written about them.

Include (3–5 items):

  • 1–3 key excerpts from the primary work(s) Whole chapters or scenes where the voice, character work, or theme is strongest.
  • 1 deep critical essay Focused on theme, character psychology, or structure (not just summary).
  • 1 craft/technique source or interview An interview or close reading that explains how the effect is achieved.
  • 1 context note using the WHY I CHOSE THIS AUTHOR template.

Avoid:

  • A single full novel with no supporting analysis.
  • Dozens of short reviews or blog posts saying the same thing.
  • Mixing more than 2 authors in one Literary Roots notebook.

Why This Notebook Matters

Every writer has literary ancestors—authors whose work feels like it was written for you. These aren’t just influences; they’re the DNA of your creative instincts.

When you study what moves you, you’re not copying. You’re learning to articulate your own taste.


What to Collect

1. Long-Form Texts (Depth)

Quantity: 1–3 stories, chapters, or essays

Source Type Where to Find It File Format
Public domain stories Project Gutenberg, Internet Archive PDF, TXT
Modern short stories Literary magazines (Granta, The Paris Review, Tor.com) PDF (save as)
Novel excerpts Your own purchased ebooks, library PDF, DOCX
Essays/craft pieces Author blogs, “On Writing” collections PDF, TXT

Tip: For copyrighted work, use excerpts you’ve legally acquired. NotebookLM is for personal research.


2. Interviews & Conversations (Rhythm)

Quantity: 1–2 interviews

Source Type Where to Find It File Format
Author interviews YouTube, podcast apps, literary festivals MP3 (audio)
Written interviews The Paris Review “Art of Fiction”, literary blogs PDF, TXT
Craft talks MasterClass clips, writing conference recordings MP3, transcript

Why Audio Works: Hearing an author talk reveals their actual voice patterns—rhythm, word choice, how they think. This feeds directly into Voice Calibration later.


3. Your Annotations (Sparks)

Quantity: 1 document

Create a document where you capture:

  • Passages you highlighted (5–10 key quotes)
  • Moments that stopped you (what made you pause?)
  • Techniques you noticed (how did they do that?)

This is your reading trace—proof of what resonated.


Source-Hunting Strategies

For Classic Authors

  1. Project Gutenberg — Full texts of public domain works
  2. LibriVox — Free audiobooks of classics (MP3 format)
  3. Internet Archive — Scanned editions, often with original illustrations
  4. University open courses — Lecture recordings analyzing the author

For Contemporary Authors

  1. Their official website — Often has essays, excerpts, event recordings
  2. Literary podcasts — Search “[Author name] interview podcast”
  3. YouTube — Festival talks, bookstore events, craft discussions
  4. Goodreads/Amazon — “Look Inside” excerpts (screenshot, then caption)

For Genre Writers

  1. Genre-specific magazines — Analog, Asimov’s (SF), Ellery Queen (Mystery)
  2. Author newsletters — Many share craft essays with subscribers
  3. Convention panels — WorldCon, Bouchercon, etc. often post recordings

Create a Saved Note in your notebook titled: WHY I CHOSE THIS AUTHOR

[!IMPORTANT] Don’t Forget: After writing this note, select it and click “Convert to Source”. The AI cannot read your Saved Notes unless they are converted into Sources!

Template:

AUTHOR: [Name]

WHY THIS AUTHOR FEELS LIKE HOME:
[2–3 sentences on what draws you to their work]

WHAT I'M LOOKING FOR:
- [ ] Craft techniques (sentence structure, pacing)
- [ ] Voice patterns (word choice, rhythm)
- [ ] Thematic approaches (how they handle big ideas)
- [ ] Character work (psychology, dialogue)

HOW THIS CONNECTS TO MY STORY:
[If you have a book idea: how does this author relate?]
[If you don't: what patterns am I noticing across my influences?]

Example:

AUTHOR: Ursula K. Le Guin

WHY THIS AUTHOR FEELS LIKE HOME:
Her prose is spare but never cold. She makes philosophy feel like plot.
I want my speculative fiction to have that same sense of ideas-as-story.

WHAT I'M LOOKING FOR:
- [x] Craft techniques (how she handles exposition)
- [x] Thematic approaches (embodied philosophy)
- [ ] Character work

HOW THIS CONNECTS TO MY STORY:
My novel deals with AI consciousness. Le Guin's "The Ones Who Walk
Away from Omelas" is the template for how to make ethical dilemmas
feel lived-in rather than preachy.

Common Mistakes

Mistake Problem Fix
Too many authors Dilutes the signal Pick 1–2 authors per notebook, max
Only collecting, never annotating AI doesn’t know what you value Add your reading trace document
Skipping the Context Note AI treats sources as random Always write “Why I Chose This”
Only grabbing famous quotes Missing the craft Capture mundane passages that work

Example Notebook Structure

Raw – Literature – Ursula K. Le Guin/
├── [VOICE] - The Left Hand of Darkness - Ch 1.pdf
├── [THEME] - The Ones Who Walk Away from Omelas.pdf
├── [CRAFT] - Le Guin on Steering the Craft (excerpt).pdf
├── [INTERVIEW] - Paris Review Art of Fiction.pdf
├── [INTERVIEW] - Guardian Long Read Audio.mp3
├── My Reading Trace - Le Guin.txt
├── Saved note copied to source - Le Guin Conversation
├── Writers_Factory_Table_Generation_Engine
└── WHY I CHOSE THIS AUTHOR (Saved Note)

It is not necessary to add the tag-words or the square brackets, they are only to help you remember what sources are important. When you do the final data export you have the opportunity to check or uncheck the sources which are to be included in the data extraction export.

What This Feeds Into

When you run the Deepening Prompts, this notebook produces:

Table What You’ll Get
character_archetypes Psychological patterns, fatal flaws, arc types
plot_structure Save the Cat beats, pacing patterns
voice_analysis Prose rhythm, metaphor domains, anti-patterns

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