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Anthropic Claude Certified Architect - Professional Sample Questions:

1. Engineering leadership wants to roll out Claude Skills to 280 developers across 14 teams. Skills will encode internal coding standards, code-review checklists, and incident-postmortem templates. Leadership has asked how to govern Skill authorship so that Skills remain trustworthy without bottlenecking on a single central team.
Which governance model should you recommend?

A) Federated authorship across the 14 teams with a central review and publication gate.
B) Fully decentralized authorship across the 14 teams with no review before publication.
C) Centralized authorship by a single platform team responsible for every Skill produced.
D) Per-developer authorship across the 280 engineers with no team-level coordination required.

2. A Claude architect is leading the discovery phase for a new AI-powered customer service solution.
Which two activities are characteristic of structured discovery and requirement gathering for a Claude-based deployment? (Select two.)

A) Facilitating stakeholder workshops to surface latency, accuracy, and compliance constraints before scoping begins.
B) Documenting explicit success criteria and failure thresholds that will gate production deployment.
C) Deferring constraint documentation until the integration design phase to avoid scope creep.
D) Generating an initial prototype and iterating based on user reaction rather than written requirements.
E) Selecting the Claude model tier based on the architect's prior project experience before stakeholder input is collected.

3. You are defining transparency practices for a customer-facing assistant whose responses are materially shaped by AI.
Which transparency practice most directly supports responsible deployment?

A) Disclose AI involvement to end users in line with the organization's transparency policy and provide a documented path to reach a human when needed.
B) Disclose AI involvement only to internal staff and operators while withholding that information from the end users whose interactions are materially shaped by the AI system.
C) Refuse to answer any user question about how the responses were produced or whether AI was involved, treating the AI's role as confidential operational information.
D) Misrepresent the AI's role in producing responses in order to make the assistant feel more trustworthy or more human, undermining informed user consent and organizational transparency.

4. When communicating an architectural decision to a security and compliance reviewer, which content set is most aligned with that audience's primary concerns?

A) Decision rationale, business outcomes, and high-level risk summary for executive review.
B) Implementation timeline, component interfaces, and deployment sequence for the engineering team.
C) Feature delivery schedule, roadmap dependencies, and scope boundaries for the product manager.
D) Threat model, control mappings, residual-risk acceptance criteria, and audit traceability.

5. You are identifying the highest-impact optimization for a deployment whose token cost is dominated by a long, repeated system prompt and a large retrieved context per request.
Which optimization most directly targets the dominant cost driver?

A) Switch every request to the heaviest available model to maximize output quality, accepting that higher per-request inference cost compounds rather than addresses the dominant cost driver.
B) Increase retrieval depth on every request to maximize recall, worsening the dominant cost driver by adding more retrieved tokens per request rather than reducing them.
C) Add additional repeated content to the system prompt to give the model more guidance.
D) Move the long, repeated system prompt into a cacheable prefix and trim retrieved context to the spans relevant to each query.

Solutions: