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Anthropic CCAR-P Exam Syllabus Topics:

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

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                    Anthropic Claude Certified Architect - Professional Sample Questions (Q35-Q40):

                    NEW QUESTION # 35
                    You are running a discovery engagement for a new Claude-based capability and must complete the requirements-gathering steps before validating with stakeholders.
                    Which two steps must be completed BEFORE validating the captured requirements with stakeholders? (Select two.) Each correct answer presents part of the solution.

                    Answer: A,D

                    Explanation:
                    Requirements must first establish what the capability is expected to accomplish, who will use it, and which constraints bound the solution. Option B captures the business purpose, success criteria, and intended user population. Option E identifies critical non-functional requirements that will influence model selection, integration patterns, deployment boundaries, evaluation design, and operational controls. These inputs must exist before stakeholders can validate whether the captured requirements accurately represent their needs.
                    Architecture decision records are produced after meaningful alternatives and design decisions exist. Detailed traceability is important but follows the initial elicitation and consolidation process. Rollout scheduling occurs later, after requirements and architecture have been validated. Anthropic likewise recommends defining measurable success criteria and empirical evaluation methods before optimizing prompts or finalizing the implementation. Anthropic: Prompt engineering overview


                    NEW QUESTION # 36
                    You are producing an architecture guide for a new deployment and must complete the planning steps before drafting each section.
                    Which two steps must be completed BEFORE drafting each section of the guide? (Select two.) Each correct answer presents part of the solution.

                    Answer: A,E

                    Explanation:
                    Effective documentation begins with audience analysis and structural planning. Identifying the audience determines the required technical depth, terminology, decision context, and operational emphasis. Defining the questions the guide must answer prevents sections from becoming generic descriptions. The outline then establishes complete coverage across architecture overview, component responsibilities, interface contracts, dominant flows, operational runbooks, and known limitations. Translation occurs only after stable source content exists. Implementation-team validation also follows an initial draft because there must be material to review. Version control, reviewers, and cadence are important governance controls, but they do not replace the two content-planning activities required before section drafting. The guide should be planned around the decisions and tasks its intended readers must perform.


                    NEW QUESTION # 37
                    You are evaluating prompting claims in a peer's design document.
                    For each claim, select yes if the claim reflects sound practice. Otherwise, select no.

                    Answer:

                    Explanation:

                    Explanation:
                    Yes, Yes, No, Yes, No
                    Zero-shot prompting is a reasonable baseline for a clearly defined closed-set classifier because the model receives both the permissible labels and their meanings. Performance should then be measured against an evaluation set before additional prompt complexity is introduced. Few-shot examples are also sound for extraction because examples containing the exact field names demonstrate the required schema and reduce formatting ambiguity. Anthropic identifies examples as one of the most reliable methods for steering output format, structure, and consistency. Prompting Best Practices Chain-of-thought is not an unconditional default. Additional reasoning is appropriate when the task requires substantive decomposition or complex judgment, but routine classification and extraction may gain little while consuming more tokens and increasing latency. The technique should be selected according to evaluated task requirements.
                    An even-handed comparison governed by explicit criteria mitigates leading-question bias by requiring symmetrical treatment of alternatives rather than presupposing a preferred conclusion. Finally, prompt validation is model-specific. New model versions may follow instructions differently, change formatting behavior, alter tool selection, or produce different latency and cost characteristics. Anthropic's migration guidance consequently recommends reevaluating prompts and workloads against the new baseline. Model Migration Guide Study Guide references/topics: Zero-shot prompting; few-shot examples; reasoning techniques; neutral framing; model migration and regression evaluation.


                    NEW QUESTION # 38
                    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.

                    Answer: C,D

                    Explanation:
                    The required sequence must reduce repeated computation without changing the information or model capability used to generate projections. Prompt caching the static 6,000-token policy preamble directly addresses the largest cost contributor while preserving the complete instruction set. Anthropic states that cache reads cost substantially less than uncached input tokens, making repeated, stable prompt prefixes an ideal caching target. Prompt Caching Caching frequently reused historical-sales chunks applies the same principle to the retrieval layer. When identical, version-controlled chunks are repeatedly fetched and supplied to the model, caching their retrieval or reusable representation eliminates redundant work while maintaining the same evidence available to the projection process. The cache must use appropriate invalidation or source-version keys so updated sales data cannot be replaced by stale content.
                    Options A and B modify the information supplied to Claude. Fewer sales chunks could remove relevant historical evidence, while truncating policy instructions could alter constraints or projection behavior. Option D introduces a model-capability change and therefore cannot guarantee unchanged accuracy without a comparative evaluation. Those interventions may be considered later, but only after representative regression testing establishes equivalence.
                    Study Guide references/topics: Cost profiling; prompt caching; retrieval caching; cache invalidation; accuracy- preserving optimization; model and context trade-offs.


                    NEW QUESTION # 39
                    You are comparing two configurations for an internal compliance Q & A assistant. Configuration X reduces top-k retrieval and uses a lighter model, lowering p95 latency by 38 percent while producing a measured 2 percent reduction in the accuracy benchmark. Configuration Y retains the existing top-k retrieval setting and heavier model, with unchanged p95 latency and no measurable change in accuracy. The deployment's stated priorities are accuracy first and latency second.
                    Which configuration is the better recommendation?

                    Answer: A

                    Explanation:
                    Configuration Y is the appropriate recommendation because architectural optimization must follow the deployment's explicitly defined priorities and acceptance criteria. Accuracy is the primary requirement for this compliance assistant, and Configuration X introduces a measured two-percent accuracy regression. That reduction cannot be dismissed as ordinary benchmark variation unless repeated evaluation establishes that it is statistically insignificant. In a compliance workload, even a small accuracy decline can increase incorrect guidance, missed policy requirements, human-review effort, and regulatory exposure. Configuration Y preserves the established accuracy level while maintaining the current latency profile. Although its latency does not improve, latency is explicitly the secondary objective. Configuration X could be reconsidered only if further testing eliminates the accuracy regression or stakeholders formally approve a revised trade-off.
                    Options C and D incorrectly impose a general preference for latency over the documented deployment priorities.


                    NEW QUESTION # 40
                    ......

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