QCon AI New York 2026 Program Committee Picks: Agent Identity, Context Costs, and Open-Source Infere

The QCon AI New York 2026 program committee highlights six sessions focusing on agent identity, managing context costs in large language models, evolving engineering organizations with coding agents, open-source inference, agent standards, and audio AI. Keynotes include Nancy Wang on agent authorization and Tejas Chopra on token compression strategies for production LLMs. The conference will explore how autonomous agents impact software security, engineering practices, and AI deployment.