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This panel addresses critical operational challenges for deploying autonomous AI agents, specifically focusing on the tension between system autonomy and necessary human oversight in production environments. Key topics include verifying AI-generated code changes, managing sensitive data exposure within RAG pipelines, and establishing clear accountability frameworks when systems fail. These discussions are essential for engineering teams navigating the transition from controlled experiments to reliable, enterprise-grade AI operations.

Sources coveringInfoQ, Viakoo, AI Alignment Forum, LessWrong

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AI in Production: What Breaks, What Works, and Who Approves it?

InfoQOctober 7, 20263 min read

On October 14, InfoQ will host a free 60-minute panel with five practitioners on running AI in production. They'll discuss agent autonomy and human approval, how to verify AI-generated changes, sensitive-data exposure, and production RAG. Registrants can submit questions and will receive the recording. By Artenisa Chatziou

Once an AI system can retrieve internal documents, generate production code, or take independent actions through tools, the engineering challenges and associated risks increase. Teams need to know what the system accessed, which actions it was permitted to take, how its output was verified, and who remains accountable when it fails. Those questions become harder in production. Coding agents move…

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