AI Workloads Need Quality Gates That Continue After Deployment
Platform Engineering, Tuesday, September 29th, 2026
AI agents can pass health checks while giving bad answers, so quality gates must keep running in production.
AI agents can stay available and fast while producing unsupported answers, misusing tools or taking inappropriate actions, so the article argues release-time testing is not enough and production quality gates should continuously track groundedness, relevance, task completion, tool use, cost and user behavior.
Those gates should be tied to decisions to alert, restrict a capability or escalate to a person, especially since multi-step agents add risk because each step can look fine while the overall result is wrong.
Platform teams should provide reusable evaluation and intervention mechanisms, while application teams define acceptable outcomes and stay accountable.