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An architect is reviewing a Claude-based candidate-screening tool prior to deployment. A stakeholder asserts that because the model was not trained on company data, no bias evaluation is necessary.
Which two responses most accurately challenge this assertion? (Select two.)

• A. Fairness testing is required only when the training dataset is known to contain protected-class labels.
• B. Bias evaluation is unnecessary when the model provider has published a responsible-use policy.
• C. The system should be evaluated on outcome-disparity metrics across protected groups before deployment.
• D. The model may carry demographic biases from pretraining that manifest in screening outcomes regardless of fine-tuning.
• E. Transparency obligations are satisfied by disclosing that an AI system is in use, without further evaluation.

You are evaluating an evaluation set used to score a Claude-based hiring-support tool. The set is drawn from one geographic region and one tenure band.
Which response is most appropriate?

• A. Continue using the narrow evaluation set drawn from one region and one tenure band because the existing benchmark scores are already high on that subset.
• B. Expand the evaluation set to cover the geographic regions and tenure bands the tool will serve, and rescore the system on the expanded set before broader release.
• C. Reduce the evaluation set further to a single demographic subgroup to simplify score interpretation, narrowing coverage rather than expanding it to match the intended user population.
• D. Discard all quantitative evaluation and replace it with qualitative impressions collected from a small, convenience-selected group that may not represent the tool's full user population.

An engineering organization is adopting Claude Code across 200 developers. A team lead proposes that AI- generated pull requests bypass standard code review for changes under 50 lines because small changes are considered low risk and review capacity is constrained.
Which two Diligence-competency objections should you raise? (Select two.) Each correct answer presents part of the solution.

• A. Line count is a poor proxy for the actual risk introduced by a code change.
• B. Removing review eliminates the verification mechanism required for AI-generated output across the workflow.
• C. AI-generated pull requests should be rejected by default across the organization.
• D. Code-review capacity should be expanded to handle every code change submitted across the team.
• E. The threshold should be increased to 200 lines to capture more changes.

A Claude-based research assistant begins producing responses that confidently contradict its retrieved source documents despite no change to the retrieval pipeline.
Which two diagnostic actions most directly identify the root cause of this behavior? (Select two.)

• A. Reduce the temperature setting to lower response variance across all query types.
• B. Switch the retrieval index to a denser embedding model to improve chunk-relevance scores.
• C. Determine whether the failure reproduces on the previous model version to test for a model mismatch.
• D. Inspect the system-prompt grounding instructions to determine whether citation constraints remain intact.
• E. Increase the context-window size to allow more retrieved chunks per query.

You are evaluating retrieval-strategy claims used by a peer team.
For each claim, select yes if the statement is generally accurate. Otherwise, select no.