The Sequence Knowledge #744: A Summary of Our Series About AI Interpretability
Introduction
This post was either an anonymous submission of an interesting paper or was written by a student; full credit remains with the author (linked).
A recap closing out a multi-week deep dive into AI interpretability in foundation models. The post argues interpretability is becoming core infrastructure as models shift from next-token predictors to agentic systems with long-horizon planning and tool use, where silent failure modes like specification gaming stop being curiosities and become operational risks.