18 published lessons with this tag.
Each atom exists in relationship to others — atomicity is about self-containment not loneliness.
The connections between things carry as much meaning as the things themselves.
Not all connections are equally strong — quantifying strength improves your model.
Connections that exist today may not have existed yesterday or may not exist tomorrow.
Concepts are nodes and relationships are edges — together they form a graph.
Your externalized thoughts are the raw material for a knowledge graph.
Relationships between ideas deserve as much attention as the ideas themselves.
A link labeled causes is more useful than a generic link labeled related.
When A links to B, B should know that A links to it — bidirectional linking reveals hidden patterns.
A densely connected area of your graph represents deep understanding.
An idea connected to nothing else is either missing links or not worth keeping.
Nodes with many connections are core concepts that deserve extra attention.
Ideas that link separate areas of your knowledge graph are especially valuable.
Following connections through your knowledge graph generates new insights.
Natural groupings in your knowledge graph show you what you know most about.
Areas where connections should exist but do not indicate knowledge gaps.
Add new nodes and edges daily and the graph becomes increasingly powerful over time.
A well-structured personal knowledge graph becomes an input that AI can leverage.