As AI systems grow more distributed and agentic, networking is becoming one of the most critical yet misunderstood layers in the AI stack. This talk demystifies emerging protocols and patterns shaping the future of open source AI infrastructure—from Anthropic’s Model Context Protocol (MCP) and Google’s Agent-to-Agent (A2A) frameworks, to RDMA and zero-copy inference. We’ll examine how these technologies affect everything from fine-tuning and multi-agent coordination to RAG and edge deployments. Through real-world use cases and architectural diagrams, attendees will learn how traditional protocols like gRPC and GraphQL are evolving for AI workloads—and where new standards are desperately needed. Most importantly, we’ll identify key open source projects and opportunities for contribution in this fast-evolving space.