Exploring AI Agent Architecture Through A2A/MCP: Insights from Jeffrey Richter

The article discusses the architecture of AI systems, focusing on components like Humans, AI Agents, AI Models, and servers. It highlights the flow of data between these elements, distinguishing between imprecise inputs (natural language, images) processed by humans or AI Models and precise inputs (structured data) that software can reliably handle. AI Agents, which execute tasks on behalf of users, leverage various specialized skills to complete tasks. The article emphasizes the role of an orchestrator in managing conversations and the need for clear communication between components. Through examples, it illustrates the complexities involved in producing precise outputs from imprecise data. The integration of standards like Google’s Agent-to-Agent and Anthropic’s Model Context Protocol is discussed as essential for interoperability among AI components. The future direction of AI technology promises enhanced capabilities and task management, underscoring the evolving landscape of AI Agent architectures.

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