Anthropic CCAR-P : Claude Certified Architect - Professional

  • Exam Code: CCAR-P
  • Exam Name: Claude Certified Architect - Professional
  • Updated: Aug 21, 2026
  • Q & A: 116 Questions and Answers

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Anthropic CCAR-P Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Solution Design & Architecture17%- Decomposition techniques for complex problem solving
- Alignment with business value, cost, performance, and SLAs
- Multi-agent systems and orchestration
- Architectural patterns
  • 1. Agentic architectures
    • 2. Augmented LLM architectures
      • 3. Workflow architectures
        - Translating business problems into Claude-based AI solutions
        - End-to-end architecture design
        Topic 2: Integration19%- Claude integration mechanisms
        • 1. Agent-to-agent integration
          • 2. API and CLI
            • 3. MCP
              - Authentication and authorization analysis
              - Enterprise system integration
              - RAG pipeline design
              • 1. Chunking
                • 2. Indexing
                  • 3. Retrieval
                    Topic 3: Evaluation, Testing & Optimization16%- Evaluation framework design
                    - System issue diagnosis
                    - Evaluation metrics and datasets
                    - Production monitoring and optimization
                    - A/B testing
                    - Cost and performance optimization
                    Topic 4: Stakeholder Communication & Lifecycle Management14%- Service-level agreements
                    - Stakeholder management
                    - Architecture documentation
                    - Solution lifecycle management
                    - Communicating architectural decisions
                    - Discovery and requirements gathering
                    Topic 5: Governance, Safety & Risk Management14%- AI safety and guardrails
                    - Regulatory and compliance requirements
                    - Security and risk management
                    - Ethical AI considerations
                    - Human-in-the-loop validation
                    Topic 6: Claude Models, Prompting & Context Engineering13%- Claude model selection and trade-offs
                    - Context window optimization
                    - Guardrails
                    - System prompts and prompt templates
                    - Prompt reuse and context engineering strategies
                    Topic 7: Developer Productivity & Operational Enablement7%- Debugging and operational issue resolution
                    - Developer enablement
                    - AI-assisted developer workflows
                    - Claude tooling configuration for teams

                    Anthropic Claude Certified Architect - Professional Sample Questions:

                    1. A platform team operates a self-hosted multi-agent system on Kubernetes that orchestrates seven specialized agents for invoice processing. The team spends approximately 40 percent of engineering capacity on infrastructure maintenance, message bus reliability, and agent state recovery. The CFO has asked you to evaluate moving to managed agent infrastructure to reclaim engineering capacity. The security officer requires that all customer financial data remain within an approved network boundary.
                    Which factor should most heavily influence your recommendation?

                    A) Whether managed agents reduce per-invoice token costs across the existing processing volume.
                    B) Whether managed agent data handling satisfies the network boundary required by security.
                    C) Whether the current seven agents map cleanly to the patterns supported by managed agents.
                    D) Whether managed agents support the current bus topology used by the platform team.


                    2. You are identifying signals that a deployment should re-enter design rather than continue iterating in place.
                    Which signal most directly indicates the need for a new design cycle?

                    A) The system's current architecture cannot meet the new requirements without changes to component responsibilities or core contracts.
                    B) A dashboard alert threshold needs a small numerical adjustment to reduce false-positive noise, which can be handled as an operational configuration change without a new design cycle.
                    C) A runbook step requires a clarification edit to improve on-call guidance accuracy, which can be handled as a documentation update without changes to component responsibilities or core contracts.
                    D) A minor copy edit is requested in a customer-facing string within the existing UI, which can be handled as a localized content change without altering component responsibilities or contracts.


                    3. You are assessing a Claude-based system whose dominant risk is silent quality drift on safety-relevant outputs after a model-version upgrade.
                    Which assessment activity most directly addresses this risk?

                    A) Maintain an adversarial evaluation set with version-attributed scoring so each upgrade is measured against the same set before promotion.
                    B) Rotate adversarial inputs randomly so no two upgrades are scored on the same set.
                    C) Disable adversarial evaluation entirely during model-version upgrade cycles to reduce evaluation cost, accepting that safety drift will go undetected until it appears in production.
                    D) Skip evaluation on each model-version upgrade and rely on user-submitted complaints to surface safety drift after the upgraded model has already served production traffic.


                    4. A Claude architect needs to ensure that a security-hardening flag cannot be disabled by any individual engineer after it is set.
                    Which configuration scope correctly enforces this requirement?

                    A) Managed configuration applied centrally and marked as non-overridable
                    B) Environment variable defined in the CI/CD pipeline only
                    C) User scope (~/.claude/settings.json) on each engineer's machine
                    D) Project scope (.claude/settings.json) committed to the repository


                    5. The platform team at Trenova Systems, Inc. needs to reduce per-query cost and p95 latency for a high-volume Claude pipeline without degrading output quality on the core use case.
                    Which two optimizations directly target both cost and latency simultaneously? (Select two.)

                    A) Enable prompt caching on the static system-prompt prefix to reduce billable input tokens on repeated calls.
                    B) Add a retrieval step that fetches the full source corpus into the context window before generation.
                    C) Route straightforward query types to a smaller, faster Claude model and reserve the full model for complex cases.
                    D) Increase max_tokens to reduce the frequency of truncated responses requiring follow-up calls.
                    E) Expand the system prompt to include additional few-shot examples on every request.


                    Solutions:

                    Question # 1
                    Answer: B
                    Question # 2
                    Answer: A
                    Question # 3
                    Answer: A
                    Question # 4
                    Answer: A
                    Question # 5
                    Answer: A,C

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