YAML is the New Dockerfile: Building AI Agent Systems with Docker cagent

Abstract

The industry is rapidly moving from single LLM applications toward systems composed of multiple agents, tools, memory layers, and workflows. But most discussions around AI agents focus heavily on frameworks and demos, while avoiding the larger systems question: what does agent infrastructure actually look like? This talk takes a cloud native and systems-oriented view of AI agents. We'll explore how ideas from distributed systems, containers, orchestration, and platform engineering are beginning to shape the next generation of AI tooling. Topics include: - Why AI agents resemble distributed systems more than chatbots - The emerging role of protocols like MCP - Declarative workflows versus imperative orchestration - Reproducibility and portability challenges in AI systems - Why infrastructure concepts like OCI artifacts and YAML workflows are reappearing in AI tooling Using Docker cagent as a concrete example rather than the centerpiece, we'll examine how modern agent runtimes are evolving toward infrastructure-style abstractions.