A Pattern Language for Knowledge Engineering with Large Language Models

Knowledge Externalization

Requires the model to expose the background knowledge it will rely on before performing the task.

Problem

Models often answer from unstated premises, producing fluent but weakly grounded judgments.

Solution

Require the model to externalize relevant principles/facts first, then bind reasoning to them. Explicit premises in context make the reasoning basis inspectable and more coherent.