Introduction
Why bother
The running vault
How to read this book
Part I: The Vault
A Plain Folder of Markdown
The five folders
Why plain text beats a database here
Git for your vault
A minimal Obsidian setup
Filling in note properties automatically
One template per note type
Folder templates
One command for a new project
Linter: keep the block tidy on save
Hands-on: create your vault
Chapter 1 Quiz
3 attempts allowed
Projects, Hub Notes and Session Notes
The hub note
The session note
Why Mistakes and Decisions get headings
Not only for code
Closing a session
Hands-on: your first project
Chapter 2 Quiz
3 attempts allowed
Resources as a Zettelkasten
One idea per note
Why small notes stay findable
Linking over filing
From Inbox to Resources
Granularity in practice
Hands-on: break up a long document
Chapter 3 Quiz
3 attempts allowed
Frontmatter as a Contract
The six properties
Who reads it
Quote values that contain colons
Summary: the field that does the most work
Linting
Hands-on: lint your vault
Chapter 4 Quiz
3 attempts allowed
Part II: The Graph
Your Vault Is Too Big to Read
Three costs of reading everything
Retrieval, not reading
What this book is not
Hands-on: price your own vault
Chapter 5 Quiz
3 attempts allowed
Installing Graphify and Turning Notes into Nodes
Installing
Extracting a vault
What a node is
How the book’s graph was built
How conventions become nodes
Hands-on: your first graph
Chapter 6 Quiz
3 attempts allowed
Edges You Can Trust
The relation vocabulary
Confidence tags
Measure your own ratio
A bad edge, caught
Filtering by trust
Hands-on: audit your edges
Chapter 7 Quiz
3 attempts allowed
Communities and Surprising Connections
How Graphify clusters
Reading the communities of second-brain
God nodes
Surprising connections
Hands-on: name your communities
Chapter 8 Quiz
3 attempts allowed
The Three Outputs
graph.json
graph.html
GRAPH_REPORT.md
Keep generated files out of the vault
Exports we don’t use
Hands-on: compare degree with the report
Chapter 9 Quiz
3 attempts allowed
Part III: Retrieval and Routing
One Home per Fact
Why copies rot
The three homes
Pointers, not copies
Story is allowed to repeat; status is not
Drift
Hands-on: find the second homes
Chapter 10 Quiz
3 attempts allowed
ICM: The Folder Is the Instructions
Interpretable Context Methodology
The routing table of second-brain
What a routing file can hold
Letting the assistant read it
Testing a routing table
Hands-on: write your routing table
Chapter 11 Quiz
3 attempts allowed
Cards That Point, Not Tell
Anatomy of a card
Status: one home, many readers
Keep it short on purpose
Updating a card
Tracing a status question
Hands-on: three cards
Chapter 12 Quiz
3 attempts allowed
Graph Recall Without AI: graphify query and call.py
Graphify’s building blocks
call.py
Graph query versus call.py
Payoffs: status, decisions and front matter
Routing first
Decisions as nodes
What front matter buys
Wiring it in
What it costs
Limits
Hands-on: build and compare
Chapter 13 Quiz
3 attempts allowed
Part IV: Living With the System
Incremental Updates
What changes, and how often
Graphify’s cache and manifest
Watching and hooks
When a full rebuild is fine
Stale edges after deletions
Measuring a full run against an incremental one
Hands-on: keep the graph fresh
Chapter 14 Quiz
3 attempts allowed
Maintenance and Anti-Patterns
The six anti-patterns
vault_doctor.py
What it found in second-brain
The weekly review
Archiving and pruning
Health metrics
Hands-on: build your doctor
Chapter 15 Quiz
3 attempts allowed
Putting It Together
The whole picture
One project, start to finish
Measuring the savings
Teams
Portability across tools and models
In the wild: kdeps
Hands-on: the complete loop
Closing
Chapter 16 Quiz
3 attempts allowed
Final Exam
Final Exam
2 attempts allowed
Appendix A: Front Matter Schema
Appendix B: Hub Note Template
Appendix C: Session Note Template
Appendix D: Project Card Template
Appendix E: ROUTING.md Template
Know Everything, Read Almost Nothing Course
Turn Your Notes into a Second Brain Your AI Can Navigate, So It Reads 5 Pages, Not 4,000
Most AI memory setups make the model read everything. This course shows you how to turn your Obsidian notes into a map of connected ideas, so your AI reads about 5 pages instead of 4,000 and spends a fraction of the tokens.
Minimum price
$149
$149
You pay
Author earns
About
About the Course
You start with Obsidian. You build a second brain from scratch or reshape the vault you already have, with a structure that holds up over years of work, personal life and side projects. Then, step by step, you turn that vault into a graph: a map of how your notes connect, which your AI can follow straight to the few notes a question needs.
Your notes grow faster than any model can read them. A personal vault passes a million words quickly. Past that point, feeding everything to the model makes it less accurate, slower and far more expensive.
Know Everything, Read Almost Nothing shows you how to build a system that knows everything but only reads what each question needs. Your vault holds the memory, the graph holds the connections, and your AI reads a handful of pages instead of thousands, spending far fewer tokens on every question.
What you will learn
- Build an Obsidian vault that stays organized and easy to search as it grows
- Write notes in a way both you and your AI can rely on
- Turn your vault into a graph of connected ideas you can trust
- Discover the clusters and surprising links hiding in your own notes
- Point your AI to the right notes first, so it stops reading everything
- Cut what your AI reads from thousands of pages to about five, and trace every answer back to a note
- Keep the whole system healthy with a simple weekly routine
Who it's for: people who keep notes in Obsidian, or want to, and use AI assistants on them. No coding background needed.
Every chapter ends with a quiz, and a final exam earns you a certificate.
Read the book: Know Everything, Read Almost Nothing
Instructor
About the Instructor
Hi, I'm Joel.
I am Dutch-Filipino Software Engineer with 20+ years of experience.
And with over 20 years in the game, I’ve seen it all and loved every minute of it.
My journey has taken me through a variety of industries, from sports streaming to cybersecurity, both in the private sector and for the Dutch government, and everything in between.
Along the way, I’ve picked up a diverse set of skills and experiences, in which I document into books.
Material
Course Material
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