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Anthropic CCAR-P Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Solution Design | - Model, architecture, context, and deployment strategy selection - Claude platform and solution architecture |
| Topic 2: Stakeholder Engagement and Solution Lifecycle | - Stakeholder discovery and architectural trade-off communication - Solution lifecycle, handoff, adoption, and operational enablement |
| Topic 3: Governance, Safety, and Risk | - Security, compliance, risk management, and governance - Safety controls and fail-closed system design |
| Topic 4: Evaluation and Optimization | - Model and architecture optimization - Evaluation design and acceptance criteria |
| Topic 5: Enterprise Integration and Production | - Enterprise integration architecture and production readiness - Cost, latency, reliability, and operational design |
Anthropic Claude Certified Architect - Professional Sample Questions:
Question 1
You are explaining the precedence of Claude Code configuration scopes to the team.
Which precedence ordering, from highest to lowest, is correct?
A. User # project # local # command-line arguments # managed
B. Project # user # managed # local # command-line arguments
C. Local # managed # user # command-line arguments # project
D. Managed # command-line arguments # local # project # user
Question 2
You are a solution architect designing a Claude-based assistant with access to 60 internal tools across multiple business domains. Loading every tool definition on every request increases token usage and time to first response.
Which design pattern best addresses this issue without sacrificing capability breadth?
A. Use a separate model call to summarize all 60 tool definitions before each user turn.
B. Apply progressive tool discovery so a curated initial subset is exposed and additional tools are loaded on demand based on the task.
C. Increase the maximum context length and load all 60 tool definitions on every request, accepting the higher token cost and latency as necessary for full capability.
D. Hard-code a fixed set of five tools per request to reduce token usage, regardless of whether those tools are relevant to the current task.
Question 3
You are presenting an architectural decision to a mixed audience that includes an executive sponsor and the engineering leads who will implement the decision.
Which presentation strategy best serves both audiences?
A. Open with a deep dive into low-level implementation details targeted at engineering leads, and stop there without addressing the business outcomes or trade-offs the executive sponsor needs.
B. Lead with the decision, the business outcomes it serves, and the trade-offs accepted; follow with the technical rationale, alternatives, and implementation implications for the engineering audience.
C. Present a single undifferentiated narrative that addresses technical and business concerns with equal weight throughout, treating both audiences as requiring the same depth on every section.
D. Skip the rationale, alternatives, and trade-off discussion entirely and simply announce the chosen decision, leaving both audiences without the context needed to implement or validate it.
Question 4
A pilot AI assistant for procurement specialists shows 89 percent first-response acceptance, but follow-up surveys reveal that specialists frequently override the assistant's vendor recommendations after considering criteria the assistant did not evaluate. The pilot owner wants to ship the assistant unchanged because of the strong acceptance rate.
Which two Discernment-competency observations should you raise BEFORE approving the launch? (Select two.)
A. The pilot duration was probably too short to demonstrate reliability across the full year.
B. The survey response rate may not be statistically representative of all specialists.
C. The unconsidered criteria represent a scope gap in the assistant's input space.
D. The acceptance rate alone proves readiness for general production use.
E. Acceptance does not establish whether recommendations remain correct after specialist review.
Question 5
You are integrating Claude Code into the team's pull-request workflow. The team wants AI-assisted review without removing human approval.
Which integration design best fits this requirement?
A. Claude Code merges every pull request automatically after completing its analysis, bypassing human approval and the existing branch-protection rules.
B. Claude Code silently deletes pull requests it assesses as low quality without posting a comment or notifying the author.
C. Claude Code disables all existing branch-protection rules to streamline the merge process, removing human approval as a required gate.
D. Claude Code reviews the pull request and posts a structured analysis as a comment, while a human reviewer retains the approval decision under the existing branch-protection rules.
Solutions:
| Question 1 Answer: D | Question 2 Answer: B | Question 3 Answer: B | Question 4 Answer: C,E | Question 5 Answer: D |






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