CONCEPT
Specificity as Knowledge
The insight, codified by William Strunk Jr. and newly urgent in the AI era, that to write with specific, concrete, definite detail is not a stylistic preference but a demonstration of actual knowledge—and that AI’s systematic preference for the general reveals, by contrast, the precise thing the human must bring to the collaboration.
Strunk’s third and deepest principle—prefer the specific to the general, the definite to the vague, the concrete to the abstract—is not, at bottom, a rule about word choice. It is a rule about the writer’s relationship to the world. The abstract sentence requires no knowledge: anyone can write “a period of unfavorable weather set in.” The specific sentence requires knowledge: the writer must know it rained, that it rained every day, and that the duration was a week. Specificity demands acquaintance with the subject; abstraction demands only facility with language. In the AI era this distinction has become the clearest line separating what the machine can supply and what the human must supply.
Large language models operate on statistical patterns, and the most probable next token is, by definition, the most general, the most common, the most expected. The specific detail—the name,