Quality Engineering for Multi-Agent AI Systems

Layer 1: Agent-Level Quality Define gold standards, measure accuracy deviation (σ_agent), detect bias and hallucinations, validate individual agent behavior within ±5-7% acceptable bounds 

Layer 2: Interaction & Coordination Quality Measure context preservation across handoffs, validate semantic coherence, test coordination mechanisms under stress, and ensure critical information propagates correctly 

Layer 3: System-Level Outcomes Evaluate end-to-end business outcome accuracy (BOA), test performance under realistic workloads, detect emergent behaviors, validate goal alignment 

Layer 4: Governance & Continuous Assurance Implement drift detection (D(t)), enforce compliance rules, maintain 100% audit trail completeness, monitor behavior over time with automated alerting 

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