One of the biggest failure modes in production AI is not the model, but the data pipeline feeding it. This talk shows how to design operational event streams that keep AI applications grounded in fresh, trustworthy state. Using lessons from large-scale distributed systems, I’ll cover freshness SLAs, lag detection tied to domain truth, replay/backfill safety, schema governance, and failure playbooks so downstream AI services don’t make decisions on stale or inconsistent data.