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Anthropic CCAR-P Exam Syllabus Topics:

Anthropic Claude Certified Architect - Professional Sample Questions:

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

2. You are running a risk assessment on a planned Claude-based deployment and must complete the inventory steps before assessing threats against assets.
Which two steps must be completed BEFORE assessing threats against assets to estimate likelihood and impact? (Select two.) Each correct answer presents part of the solution.

A) Recommend mitigations and residual-risk acceptance for risks that remain.
B) Enumerate the threat actors and attack vectors relevant to the deployment.
C) Document the assessment outcome with risks, mitigations, residual risk, and acceptance owners.
D) Identify the assets that the deployment touches, along with the sensitivity of each asset.
E) Recommend mitigations and residual-risk acceptance for the risks that remain after analysis.

3. You are transitioning a Claude-based deployment from design into implementation.
Which handoff package most directly supports a clean transition?

A) The most recent set of design presentation slides without component-level diagrams, interface contracts, an evaluation framework with a reference set, runbooks, or a known-limitations register.
B) A verbal walkthrough conducted on the day of handoff with no written architecture overview, ADRs, component contracts, evaluation framework, runbooks, playbook, or known limitations.
C) Source code alone with no integrating architecture overview, ADRs, component contracts, evaluation framework, runbooks, on-call playbook, or known-limitations register to support the delivery team.
D) Architecture overview, ADRs, component contracts, evaluation framework with reference set, runbooks, on-call playbook, and known limitations.

4. You are integrating human review into a high-volume classification pipeline where reviewing every output is infeasible.
Which sampling strategy best balances throughput with quality oversight?

A) Risk-stratified sampling that reviews all low-confidence and high-impact outputs and a smaller random sample of high-confidence routine outputs.
B) Inverse sampling that reviews only high-confidence routine outputs and skips low-confidence and high- impact outputs.
C) No sampling, relying entirely on user complaints to reveal quality and safety problems after they affect users.
D) Universal review of every output regardless of confidence or throughput impact.

5. A revenue projection assistant has missed its monthly cost target by 38 percent. Profiling shows three contributors: a 6,000-token policy preamble repeated on every call (45 percent of cost), retrieval of historical sales chunks averaging 3,000 tokens per call (30 percent), and inference on a flagship-tier model (25 percent).
Stakeholders require that projection accuracy remain unchanged.
Which two optimizations should you sequence first to reduce cost without affecting accuracy? (Select two.) Each correct answer presents part of the solution.

A) Reduce the number of historical sales chunks retrieved across each query run.
B) Truncate the policy preamble to remove non-essential clauses from the prompt.
C) Cache common retrieved sales chunks accessed across many of the daily queries.
D) Enable prompt caching on the static policy preamble across the recurring calls.
E) Switch the workload to a smaller, faster Claude model tier across all queries.

Solutions: