에이전트 AI 운영화: 기업 인프라를 위한 Day 0-2 청사진

It reasons, calls tools, and returns answers in the demo that impress everyone. But between that notebook and a production deployment sits a gap having nothing to do with your model or your framework. Three failures hit a single AI agent deployment overnight—43 duplicate tickets, $4,000 charged to the wrong account, and a hallucinated refund policy leading to a $280 return the company had to honor. The agent ran on LangChain. It worked perfectly in staging. Every failure was an infrastructure failure, not an intelligence failure.

I've watched teams spend months closing that gap by hand—wiring identity, bolting on tracing, building bespoke governance. Some give up and move to a hyperscaler platform offering a guided path from experiment to production. They also get the lock-in. Bring your own agent (BYOA) is Red Hat AI's approach: the platform provides production infrastructure for any agent framework without code changes. The question isn't whether your agent needs production infrastructure, it's how your team gets there.

This article follows a team through each phase using Red Hat's own production agents as proof the platform works, because the most credible evidence is that Red Hat deploys its own production agents on this platform. Day 0 answers the question: will this work for our use case? The goal is to answer it before committing engineering resources to operationalization. Gen AI studio (a governed sandbox within Red Hat AI for experimenting with models, agents, Model Context Protocol (MCP) servers, and guardrails before deployment) provides the Day 0 environment.

A team can point an agent at different open-weight models running on vLLM (a self-hosted inference engine providing OpenAI-compatible endpoints), connect MCP servers to see what tools the agent can reach, and apply NVIDIA NeMo Guardrails to test safety behavior—all in a governed space where experiments don't touch production data or production infrastructure. I think of it as the lab bench: real reagents, real equipment, no risk of contaminating the production line. For teams that know which framework they want, starter kits provide the Day 0 starting point.