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Applying SLO error budgets to AI agent hallucination rates
- Platform/SRE — Learn: Grafana’s approach maps traditional SLO/error-budget mechanics onto agent evaluation scores, giving SREs a familiar reliability framework for operating AI systems; no production change needed today, but worth reviewing before instrumenting any agent workloads.
- CI/CD — Skip
- Leader — Learn: Framing agent quality as an error budget (measurable, target-driven) is a useful mental model for leaders deciding how to set reliability expectations and observability standards for AI agent initiatives.
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