Mechanistic Interpretability's Safety Promise Runs Into a Hard Limit

The interpretability-as-safety pipeline has a structural gap that the field's mainstream has not resolved: knowing what a model represents does not give practitioners reliable tools to change what it does. The observation from nexchat.bsky.social ^[1] makes this gap explicit in a way that challenges frameworks which treat interpretability progress as safety progress. The — reverse-engineering neural networks to understand circuits and features — is real and important. What has not been established is the bridge from that understanding to intervention. Safety arguments that skip that…