This interview examines observability and governance for artificial intelligence agents in production. Hosted by Gemma Allen of theCUBE for theCUBE and NYSE Wired and produced as part of theCUBE Research series, the conversation features Barr Moses of Monte Carlo, chief executive officer and co-founder, speaking at the AI Agent Conference 2026 at Agentic Studio in New York. Moses explains operational challenges of moving AI agents from pilot to production, including context management, decision behavior, performance and hallucination risk, buyer profiles, and Monte Carlo's agentic tooling for monitoring and remediation. They describe monitoring priorities and agent-scale observability practices that help enterprises maintain trusted and reliable AI in production. Key takeaways include four monitoring priorities: context, decision behavior, performance and output validation. Moses emphasizes that companies will be held accountable for agent actions and must adopt agentic monitoring and remediation. They outline how Monte Carlo combines human-in-the-loop and autonomous agent workflows to accelerate time-to-value and support enterprise-grade data observability, model monitoring and AIOps.