Question
A team is working in Microsoft Foundry to test and compare large language model (LLM) prompt variants in a development environment.
The team requires consistent inputs to evaluate prompt variants without relying on live user traffic.
You need to create a controlled evaluation of input data.
Which action should you perform first?
- A. Generate synthetic interaction data. Correct
- B. Configure content filters.
- C. Apply a blocklist.
- D. Enable observability metrics.
Explanation
Without production traffic, Microsoft Foundry lets you generate a synthetic evaluation dataset (or simulate interactions) so every prompt variant is scored against the same, repeatable set of inputs. That dataset is the starting point for a controlled evaluation. Content filters and blocklists control what content is allowed through, not what inputs are evaluated, and observability metrics measure behaviour after inputs exist rather than creating them.
