Metal to Agents: Bridging the Production Gap for Agentic AI

The enterprise AI landscape is rapidly shifting from simple chatbots running on LLMs to agentic AI; autonomous systems capable of reasoning, planning, and executing complex, multi-step tasks. While adoption is skyrocketing—with Gartner predicting 40% of enterprise applications will feature task-specific agents by 2026—most organizations remain stuck in the pilot phase. The challenge is the ""Production Gap"": the massive delta between an agent that works on a developer's laptop and one that runs securely, at scale, and with full audit trails and compliance in a data center. In this episode, we explore how Red Hat AI ""connects the dots"" to bridge this gap. We will move beyond the hype of framework selection to focus on AgentOps—the essential production infrastructure required for enterprise-grade autonomous action. Join our experts as we dive into a full-stack, "Metal to Agents" approach that secures the entire AI lifecycle, starting at the Linux kernel and extending to the agent runtime.