After deploying a multi-agent customer-email system in Microsoft Fo…

Question

After deploying a multi-agent customer-email system in Microsoft Foundry, quality fluctuates weekly. You need continuous improvement beyond occasional manual spot checks. Which evaluation approach best fits?

Accepted Answer

Implement continuous improvement using LLM-as-a-judge evaluations, targeted human review in Foundry, synthetic test sets, and user feedback loops to detect regressions in memory, tools, prompts, and end-to-end workflows — D is the continuous improvement stack: LLM-as-a-judge for scalable scoring, human review where it matters in Foundry, synthetic data for coverage, and user feedback loops. That matches evaluate/optimize skills for multi-agent solutions—including evaluations for memory, knowledge, tools, and prompts. A, B, and C are how quality dies quietly. Automate evals in CI/CD for agent changes, and keep humans on high-risk samples.

Answer

Never measure quality after go-live because production traffic is the only test that matters

Answer

Replace all human review with coin-flip acceptance of agent outputs

Answer

Ship prompt changes with no regression suite and rely on user complaints as the KPI

After deploying a multi-agent customer-email system in Microsoft Foundry, quality fluctuates weekly. You need continuous improvement beyond occasional manual spot checks. Which evaluation approach best fits?

Short Explanation

Full Explanation