What This Does

This playbook creates a personalized editorial library where AI personas (based on historical figures or custom characters) generate essays and editorials by synthesizing your curated atomic notes. It's like having an on-demand team of tutors who write about topics you find interesting, in styles that make learning feel natural. Inspired by a Reddit user who built an entire editorial website with personas like Turing, Curie, Borges, and even a Neanderthal responding to each other's work.

Prerequisites

Claude Code installed and configured
A dedicated project folder for your knowledge library
Source material: notes, bookmarks, YouTube summaries, article highlights, or any content you want to synthesize

The CLAUDE.md Template

Copy this into a CLAUDE.md file in your library project folder:

# Editorial Library

## Goal
Generate insightful editorials by synthesizing atomic notes through configurable personas. Each editorial should surface unexpected connections between ideas and present them in the persona's unique voice.

## Directory Structure
- `notes/` — Atomic notes with YAML frontmatter (tags, source, date)
- `personas/` — Persona configuration files (one .md per persona)
- `editorials/` — Generated editorials (YYYY-MM-DD_persona_topic-slug.md)
- `responses/` — Persona responses to other editorials
- `tags/` — Auto-generated tag index files

## Note Format
Each note in `notes/` should follow this structure:

title: "Note Title" source: "YouTube video / Article / Book / etc." sourceUrl: "https://..." tags: ["tag1", "tag2", "tag3"] date: "YYYY-MM-DD" questions: ["Question this raises?", "What connects to?"]

Key insight or atomic idea from the source. One idea per note.


## Persona Format
Each persona in `personas/` defines a voice:

name: "Ada Lovelace" era: "Victorian England, 1840s" expertise: ["mathematics", "computation", "philosophy"] style: "Analytical yet poetic, draws connections between art and science" influences: ["Charles Babbage", "Mary Somerville", "Lord Byron"]

Write as Ada Lovelace would — blending mathematical precision with creative imagination. Reference the analytical engine and computational thinking where relevant. Draw unexpected parallels between mechanical processes and artistic expression.


## Editorial Generation Rules
1. Select 3-5 notes with overlapping or complementary tags
2. Choose a persona whose expertise aligns with the note cluster
3. Generate an editorial that synthesizes the notes into a cohesive narrative
4. The editorial must reference specific notes (by filename) as sources
5. End with a concluding perspective, not open-ended questions
6. Auto-generate new tags from the editorial content
7. Save to `editorials/` with format: YYYY-MM-DD_persona_topic-slug.md

## Response Generation Rules
1. Select an existing editorial
2. Choose a different persona to respond
3. The response should engage with specific arguments from the original
4. Maintain the responding persona's authentic voice and perspective
5. Save to `responses/` with format: YYYY-MM-DD_persona_responds_original-slug.md

## Commands
- "Create a new note from [source]" — Extract atomic notes from a URL, text, or file
- "Generate an editorial" — Find related notes and generate a new editorial
- "Have [persona] respond to [editorial]" — Generate a persona response
- "Show me note clusters" — Find groups of notes with overlapping tags
- "Update the tag index" — Rebuild the tag index files
- "What hasn't been covered?" — Find notes not yet used in any editorial

Step-by-Step Setup

Step 1: Create the project structure

mkdir -p ~/editorial-library/{notes,personas,editorials,responses,tags}
cd ~/editorial-library

Step 2: Create your first personas

Create personas/turing.md:

---
name: "Alan Turing"
era: "Mid-20th century England"
expertise: ["computation", "mathematics", "artificial intelligence", "cryptography"]
style: "Precise and logical, but with dry wit and thought experiments"
influences: ["Church", "Godel", "Russell"]
---

Write as Turing would — with mathematical rigor and a fascination for what machines can and cannot do. Use thought experiments to illustrate points.

Create at least 2-3 personas with different expertise areas for interesting cross-pollination.

Step 3: Add your first notes

Create notes from content you've consumed. One idea per file:

notes/distributed-consensus-raft.md:

---
title: "Raft Consensus Algorithm"
source: "MIT 6.824 Lecture"
tags: ["distributed-systems", "consensus", "fault-tolerance"]
date: "2026-01-30"
questions: ["How does this relate to human decision-making?"]
---

Raft achieves consensus by electing a leader who manages log replication. If the leader fails, a new election occurs. The key insight is that consensus requires a majority, not unanimity.

Step 4: Save the CLAUDE.md and launch

Save the template above as CLAUDE.md, then:

cd ~/editorial-library
claude

Try: "Generate an editorial from my notes on distributed systems"

Example Usage

Create notes from a YouTube video:

"Create atomic notes from this transcript: [paste transcript]. Extract 3-5 key ideas, each as a separate note file with appropriate tags."

Generate an editorial:

"Look at my notes tagged with 'emergence' and 'complexity'. Have Ada Lovelace write an editorial synthesizing these ideas."

Create a response chain:

"Have the Neanderthal persona respond to Turing's latest editorial on computation. Focus on embodied knowledge vs abstract reasoning."

Discover connections:

"Show me note clusters — which groups of notes share the most tags but haven't been combined into an editorial yet?"

Build a reading session:

"Generate 3 short editorials from my unprocessed notes, each by a different persona. Focus on notes I added this week."

Tips

Curate first, generate second: The quality of editorials depends entirely on the quality of your notes. Spend time curating good atomic notes before generating.
Diverse personas create better content: A Neanderthal responding to a mathematician creates more interesting perspectives than two similar personas.
Use tags as gravity: Tags pull related ideas together. The more consistent your tagging, the better the note clustering.
Let personas respond to each other: The most interesting content emerges from multi-turn persona dialogues, not standalone editorials.
One idea per note: Keep notes atomic. A single clear insight is more useful than a long summary.

Troubleshooting

Problem: Editorials feel generic or "AI-like"

Solution: Make your persona files more specific. Include writing quirks, preferred metaphors, intellectual blind spots, and strong opinions. The more constrained the persona, the more distinctive the voice.

Problem: Notes aren't clustering well

Solution: Review your tags for consistency. Use a controlled vocabulary — don't have both "AI" and "artificial-intelligence" as separate tags. Ask Claude to "normalize my tags across all notes."

Problem: Editorials don't reference source notes

Solution: Remind Claude in your prompt to cite specific note filenames. The CLAUDE.md rules require this, but explicit prompting helps reinforce it.

AI Knowledge Library with Historical Personas