Frequently asked questions about thinking, epistemology, and cognitive tools. 1480 answers
Dividing things into only two groups forces a false simplicity.
Tracing a chain of causes and effects reveals the full mechanism behind an outcome.
Multiple paths between important nodes make a system more robust.
Select a prediction you made in the last six months that turned out wrong. Write it down with as much specificity as you can: what you predicted, what actually happened, and the gap between the two. Now perform a schema autopsy. Do not ask "what did I do wrong?" Ask "what does this prediction.
Two opposite failure modes bracket this lesson. The first is treating failed predictions as evidence of personal inadequacy — collapsing the distance between "my model was wrong" and "I am wrong." This triggers ego defense, avoidance of future predictions, and schema stagnation. The second failure.
When your prediction is wrong you have learned something about where your schema is off.
Looking for evidence that supports your schema is not the same as rigorously testing it.
You can build schemas at different levels of abstraction each serving different purposes.
Concepts are nodes and relationships are edges — together they form a graph.
Choose five concepts you have been studying or thinking about recently — from any domain. Write each one on a separate card or sticky note. These are your nodes. Now draw lines between every pair that has a meaningful relationship. Label each line with the nature of the relationship: "causes,".
Treating nodes and edges as purely technical vocabulary — something that belongs to computer science or mathematics but not to how you actually think. This creates a wall between "graph theory" and "my knowledge," when the entire point is that your knowledge already has graph structure. You.
Concepts are nodes and relationships are edges — together they form a graph.
Areas where connections should exist but do not indicate knowledge gaps.
Something can be true now and have been false before without contradiction.
Find a belief you hold now that contradicts something you believed three or more years ago. Write both versions down with dates: 'In [year], I believed [X]' and 'Now, in 2026, I believe [Y].' Then answer three questions: (1) What changed in the environment between then and now? (2) What changed in.
Assuming that because your current belief contradicts a past belief, one of them must have been wrong. This is presentism — judging past reasoning by present conditions. The subtler failure is the opposite: assuming your current beliefs are as time-bound as the ones they replaced, and therefore.
Something can be true now and have been false before without contradiction.
Assigning types to objects restricts what operations make sense on them.
Items that do not fit neatly into any category expose weaknesses in your system.
Choose a domain you organize — your notes, your project files, your reading list, your skill inventory. Pick five items and ask: does each item have exactly one parent, or does it genuinely belong in multiple categories? For each item with multiple natural parents, write down all the parents it.
Forcing lattice-shaped knowledge into tree-shaped containers. This happens constantly in practice. A team creates a folder structure for documentation and discovers that the "API Authentication" document belongs in both the "Security" folder and the "API Reference" folder. They pick one — say,.
Real knowledge often has items that belong to multiple parent categories. When you force every concept into a single branch of a tree, you destroy information. Lattice structures — where a node can have multiple parents — preserve the multidimensional nature of knowledge. The tree is a special.
Your risk model determines what you attempt and what you avoid.
The gap between what you say you value and what you actually do is the most important contradiction to examine.