Ops used to be a world of YAML, caffeine, and careful deploy rituals. Now it’s probabilistic models, token-based cost surprises, and reliability questions that sound more like, “Will the model mean the same thing tomorrow?” In this episode of Pop Goes the Stack, Lori MacVittie and Joel Moses dig into what happens when production expectations collide with non-deterministic AI systems, and why the next phase of automation needs more than a chat interface and optimism.

They’re joined by John Capobianco from Itential to explore “VibeOps,” an approach to conversational operations that doesn’t throw away deterministic workflows, but connects them to agent reasoning, tool calling, and modern protocols like MCP. The discussion breaks down agent “skills” as a way to describe what an agent can do, constrain what it can’t, and build guardrails in a format teams can manage.

From red-teaming experiments to real-world concerns about failure rates at scale, the conversation stays grounded in what it takes to make AI useful in production: external knowledge, policy alignment, composable skills, and a maturity path from lab-only to read-only to supervised execution, and only then toward autonomy. The takeaway is clear: conversational ops can accelerate work, improve documentation and ticket quality, and reduce toil, but governance and accountability still matter. If you’re navigating AIOps, agent adoption, or the post-MCP tooling wave, this episode offers a realistic starting point.