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Anthropic CCAR-P Exam Syllabus Topics:

Anthropic Claude Certified Architect - Professional Sample Questions:

1. You are designing a test strategy for a Claude-based pipeline that handles sensitive financial data.
Which two test types should be prioritized to cover both safety under attack and cross-component correctness? (Select two.)

A) Integration tests that verify end-to-end pipeline behavior across all components.
B) Unit tests targeting only individual prompt-template rendering logic.
C) Adversarial tests using prompt-injection and malformed-input cases.
D) Regression tests against a stable reference set of previously known-good outputs.
E) Smoke tests that verify core paths after each deployment.

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

3. You are classifying token-management tactics by where each tactic applies in the request lifecycle: "Input Preparation," "Prompt Construction," or "Output Handling."

4. A loan pre-qualification assistant shows 94 percent approval recommendations that match the human underwriter decision. The fairness team has reviewed approval rate parity across protected groups and reported no significant difference. A board member has asked whether this evidence is sufficient to declare the assistant fair.
Which two Discernment-competency findings should you report? (Select two.) Each correct answer presents part of the solution.

A) The fairness team's review process likely missed at least some of the protected groups studied.
B) Approval rate parity does not by itself assess error rate parity across protected groups.
C) The 94 percent match rate is sufficient evidence of fairness for the assistant's decisions.
D) Match with human underwriters does not establish freedom from underwriter-introduced bias.
E) A larger sample is needed before any meaningful fairness claim can be made about the model.

5. A security audit uncovers two issues: (1) all end users share a single API key, and (2) tool calls are executed without logging the initiating user.
Which two mitigations directly address these specific findings? (Select two.)

A) Replace the shared API key with per-user OAuth tokens carrying scope-restricted permissions.
B) Add actor attribution to tool-call logs so each call records the initiating user identity.
C) Move credentials out of the prompt context and resolve them from a server-side secret store.
D) Enforce RBAC at the retrieval layer before content enters the model context.
E) Validate structured outputs against a schema before downstream actions are executed.

Solutions: