Inference is the New Training Loop: Architecting High-Reliability Agents and Continuous AI Systems

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Official Description

For agentic AI and complex, multi-step workloads, the inference environment is the engine for

continuous improvement, not a final deployment step. This talk focuses on engineering the full AI

loop: tightly integrating inference with reinforcement learning (RL) and evaluation. Learn how to

leverage native observability, serverless RL, and optimized inference stacks to continuously refine

model behavior based on production traces, delivering agents that are reliable, auditable, and

constantly evolving.

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