What are some ways to avoid common methological pitfalls when generating test cases for "groundedness" benchmarks with automation? Confirmation bias is one obv

What are some ways to avoid common methological pitfalls when generating test cases for "groundedness" benchmarks with automation? Confirmation bias is one obvious pitfall that comes to mind, but also I wonder how it is possible to achieve reproducibility when the input is stochastic.