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| Section | Weight | Objectives |
|---|---|---|
| Developer Productivity & Operational Enablement | 7% | - Debugging and operational issue resolution - Developer enablement - AI-assisted developer workflows - Claude tooling configuration for teams |
| Solution Design & Architecture | 17% | - Architectural patterns
- Decomposition techniques for complex problem solving - End-to-end architecture design - Alignment with business value, cost, performance, and SLAs - Translating business problems into Claude-based AI solutions |
| Claude Models, Prompting & Context Engineering | 13% | - Context window optimization - Prompt reuse and context engineering strategies - System prompts and prompt templates - Claude model selection and trade-offs - Guardrails |
| Evaluation, Testing & Optimization | 16% | - System issue diagnosis - Production monitoring and optimization - Evaluation framework design - Evaluation metrics and datasets - Cost and performance optimization - A/B testing |
| Stakeholder Communication & Lifecycle Management | 14% | - Communicating architectural decisions - Discovery and requirements gathering - Stakeholder management - Service-level agreements - Architecture documentation - Solution lifecycle management |
| Integration | 19% | - Claude integration mechanisms
- RAG pipeline design
|
| Governance, Safety & Risk Management | 14% | - Security and risk management - AI safety and guardrails - Regulatory and compliance requirements - Human-in-the-loop validation - Ethical AI considerations |
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Exam4Docs's Anthropic CCAR-P exam questions pdf is formed in a proper way that gives candidates the necessary asthenic unformatted data required to pass the Anthropic exam. The study materials highlight a few basic and important questions that are repeatedly seen in past Anthropic exam paper sheets. The Anthropic CCAR-P Practice Questions are easy to access and can be downloaded anytime on your mobile, laptop, or MacBook.
NEW QUESTION # 53
You are classifying chunking strategies by the corpus type each is best suited to.
For each chunking strategy, select the appropriate corpus type: "Long Structured Documents,"
"Heterogeneous Short Records," or "Code or Hierarchical Specifications."
Answer:
Explanation:
Explanation:
* Function-level or section-level chunking for code modules - Code or Hierarchical Specifications
* Tree-aware chunking that follows code or specification hierarchy - Code or Hierarchical Specifications
* Per-record chunking where each record is one chunk - Heterogeneous Short Records
* Semantic chunking along clause or paragraph boundaries - Long Structured Documents
* Fixed-size chunking with overlap for short records of similar length - Heterogeneous Short Records
* Hierarchical chunking that mirrors document section structure - Long Structured Documents Chunking must preserve the structural unit that carries meaning in the source corpus. Code and hierarchical specifications are best divided at function, module, class, or tree boundaries because arbitrary token cuts can separate definitions from their implementation or parent context. Heterogeneous short-record collections should generally preserve each record as an independent chunk. Fixed-size overlapping chunks are also effective when records have broadly similar lengths and lack meaningful internal hierarchy. Long structured documents benefit from semantic boundaries such as clauses and paragraphs, while hierarchical chunking preserves relationships among sections, subsections, and parent headings. Anthropic notes that chunk size, boundaries, and overlap materially affect retrieval performance; therefore, one universal chunking method is inappropriate. Anthropic Contextual Retrieval
NEW QUESTION # 54
You are supporting an engineer whose newly added MCP server does not appear in their Claude Code session.
Which diagnostic step should be tried first?
Answer: C
Explanation:
The first diagnostic action must establish whether Claude Code has loaded the MCP server configuration and whether it can connect to the registered endpoint. The official management command is claude mcp list; within Claude Code, /mcp can also be used to inspect server status. The listing distinguishes registered and connected servers from configurations that require authentication, approval, or connection troubleshooting.
Connect Claude Code to Tools via MCP
If the server was added or its configuration changed after the current session began, reconnecting or restarting the relevant Claude Code session is a proportionate next step. This ensures that configuration state and available tool definitions are refreshed before more intrusive troubleshooting begins. If the server is listed but unhealthy, the engineer can then inspect it with claude mcp get < name > and investigate transport, command path, credentials, workspace approval, or endpoint connectivity.
Options A, B, and D are operationally unsound because they discard working capabilities or environments before confirming the basic registration state. Disabling all MCP servers eliminates useful diagnostic comparisons; changing product families abandons the relevant configuration; reinstalling the operating system is grossly disproportionate and risks destroying evidence needed for diagnosis.
Study Guide references/topics: Claude Code environment configuration; MCP registration; server-status inspection; session refresh; targeted operational troubleshooting.
NEW QUESTION # 55
You are selecting a model for a new production workload and must complete the upstream steps before testing candidate models empirically.
Which two steps must be completed BEFORE running a representative sample on a candidate model? (Select two.) Each correct answer presents part of the solution.
Answer: D,E
Explanation:
Empirical model testing requires a defined decision frame. Option D must occur first because the quality threshold, acceptable latency, expected request volume, and associated cost envelope determine what constitutes a successful result. Without these criteria, a representative-sample test can produce measurements but cannot support a defensible selection.
Option C is the next upstream step. Known model capabilities and the workload profile are used to identify a plausible candidate rather than testing models arbitrarily. Anthropic's model-selection guidance recommends evaluating capability, speed, cost, and effort requirements before narrowing the candidate set. Choosing the Right Model Option A occurs after empirical testing because the architect cannot know which lightest model consistently meets the quality bar until sample results have been evaluated. Option B belongs to ongoing lifecycle management after a new version becomes available. Option E is a deployment-governance activity that follows successful model selection, security review, and readiness validation.
The correct sequence is: define workload criteria, shortlist candidate models, run a representative evaluation, compare quality and operational metrics, select the least costly model that reliably satisfies all gates, and periodically retest the decision.
Study Guide references/topics: Requirements-driven model selection; representative sampling; quality thresholds; latency and volume requirements; capability-cost trade-offs; model lifecycle reassessment.
NEW QUESTION # 56
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 # 57
You are a solution architect evaluating candidate use cases for a Claude-based program.
For each scenario, select Yes if Claude is appropriate as the primary solution at the architectural level.
Otherwise, select No.
Answer:
Explanation:
Explanation:
* Drafting first-pass investigative reports from semi-structured incident logs for analyst review - Yes
* Computing real-time fraud scores at sub-50-millisecond latency on a streaming pipeline - No
* Long-context contract review with structured clause extraction and deviation flagging - Yes
* Replacing a vector index for semantic retrieval over a multi-million-document corpus - No
* Routing inbound support tickets into 30 categories with reasoning for the selected route - Yes Claude is well suited to language-intensive analysis, summarization, extraction, classification, and drafting.
Investigative-report drafting, contract analysis, and support-ticket routing all require interpretation of unstructured or semi-structured language and can incorporate human review. A sub-50-millisecond fraud- scoring path requires deterministic, specialized real-time processing and should not place LLM inference on the critical path. Claude also does not replace the retrieval index used to search millions of documents; it consumes the results produced by that infrastructure. The correct architectural decision separates tasks requiring semantic language reasoning from deterministic computation and information-retrieval infrastructure. Model selection and evaluation must then confirm that the chosen Claude model satisfies quality, latency, and cost requirements.
NEW QUESTION # 58
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