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This is a conference preview, but its substance is AI: how agents should be authorized and how to control LLM context costs in production. The picks show that practitioners see agent identity and token efficiency as real bottlenecks for agentic software, not just research topics. Readers should treat the session list as a signal of production concerns, not as evidence that these problems are solved.
QCon AI New York 2026 Program Committee Picks: Agent Identity, Context Costs, and Open-Source Infere
Who authorizes an agent’s actions, and how should teams manage growing context costs? The QCon AI New York 2026 program committee shares six session picks that tackle these questions, alongside open-source inference, agent standards, and audio AI. By Artenisa Chatziou
Who authorizes an agent’s actions? How should teams manage growing context costs? What changes when coding agents become part of everyday engineering work? The QCon AI New York 2026 program committee has selected six sessions they are looking forward to at the December 15–16 conference. Their picks examine these questions alongside open-source inference, agent standards, and audio AI. Conference chair Hien Luu, an AI/ML leader, advisor, speaker, and author, joins committee members Wes Reisz, Technical…
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