Mechanistic interpretability — Mechanistic interpretability is research that tries to reverse-engineer neural networks into understandable parts and processes. Researchers identify specific features and circuits inside a model and show how they produce behavior. Anthropic and others have mapped millions of features in large models. The goal is to understand models as well as engineers understand ordinary software.

Added October 21, 2026