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This article focuses on the operational shift from prompt engineering to building robust production infrastructure for AI agents, covering critical themes like context management, security harnessing, and state control. It highlights how teams are moving toward shared platform layers that define core architecture rather than treating these capabilities as optional features. The content addresses essential challenges in deploying reliable, scalable agent systems within real-world environments.

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QCon AI Boston: Production AI Moves beyond Prompts to Platforms, Harnesses, and Evals

InfoQJuly 17, 20264 min read

QCon AI Boston 2026 focused on the operational challenges of deploying AI agents, emphasizing the need for robust production infrastructure. Key themes included improving context management, ensuring security through a "harness" around agents, and adopting a comprehensive engineering model for AI. By Tatiana Fesenko

QCon AI Boston 2026 marked a turning point. We have spent the last couple of years learning to build AI agents. Now the question is how to run them, safely and reliably, once they are live. Almost every talk came back to the same theme: agents are forcing teams to build real production infrastructure around them. OpenAI’s Martin Spier set the tone in the opening keynote.…

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