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| Section | Weight | Objectives |
|---|---|---|
| Claude Models, Prompting & Context Engineering | 13% | - System prompts and prompt templates - Claude model selection and trade-offs - Guardrails - Prompt reuse and context engineering strategies - Context window optimization |
| Governance, Safety & Risk Management | 14% | - Human-in-the-loop validation - Regulatory and compliance requirements - Security and risk management - AI safety and guardrails - Ethical AI considerations |
| Solution Design & Architecture | 17% | - Decomposition techniques for complex problem solving - Alignment with business value, cost, performance, and SLAs - Translating business problems into Claude-based AI solutions - Architectural patterns
- End-to-end architecture design |
| Evaluation, Testing & Optimization | 16% | - Evaluation metrics and datasets - Evaluation framework design - A/B testing - Cost and performance optimization - Production monitoring and optimization - System issue diagnosis |
| Stakeholder Communication & Lifecycle Management | 14% | - Service-level agreements - Stakeholder management - Discovery and requirements gathering - Architecture documentation - Communicating architectural decisions - Solution lifecycle management |
| Integration | 19% | - RAG pipeline design
- Claude integration mechanisms
|
| Developer Productivity & Operational Enablement | 7% | - Debugging and operational issue resolution - Developer enablement - AI-assisted developer workflows - Claude tooling configuration for teams |
>> Valid Anthropic CCAR-P Exam Format <<
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NEW QUESTION # 10
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 # 11
A Claude architect is designing a HIPAA-compliant pipeline that processes patient records.
Which two design decisions directly support HIPAA compliance requirements? (Select two.)
Answer: C,E
Explanation:
Role-based access control directly supports HIPAA's access-control and minimum-necessary principles. The retrieval and orchestration layers must verify the authenticated user's role before protected health information enters the model context. Authorization should be applied to individual records, data sources, tools, and actions, with audit events recording the requesting identity, accessed resource, purpose, and result. Model instructions alone are not a security boundary.
Patient information must also remain within services and processing activities covered by the organization's Business Associate Agreement. Anthropic states that PHI processing requires a HIPAA-ready organization and an accepted BAA, and that only specified eligible services and configurations are covered. Patient data must not be submitted through training, feedback, beta, third-party, or integration pathways that fall outside the applicable agreement. A BAA is not blanket authorization; architects must verify feature eligibility and disable inappropriate data-sharing mechanisms.
Reducing max_tokens, selecting a more capable model, and enabling streaming affect output length, quality, or latency. They do not establish authorization, contractual coverage, minimum-necessary access, or compliant PHI handling.
Study Guide references/topics: Anthropic Business Associate Agreement requirements ; HIPAA-ready services; PHI access control; minimum necessary; eligible-service boundaries; auditability.
NEW QUESTION # 12
The compliance team at a firm has approved a Claude Skill that generates client-facing investment summaries. The Skill includes the firm's required disclaimers and prohibited-language list. A product manager has asked whether additional guardrails are needed at the application layer or whether the Skill alone is sufficient.
Which two guardrail responsibilities should remain at the application layer rather than the Skill? (Select two.) Each correct answer presents part of the solution.
Answer: C,D
Explanation:
Authorization and compliance logging must remain enforceable application-layer controls. Option B requires the application to authenticate the requester, resolve the user's role and entitlements, and deny the operation when the user lacks authority. A Skill can instruct Claude how to behave, but it is not a reliable security boundary and cannot replace identity-based access control enforced by the surrounding system.
Option A similarly belongs at the application layer. The application must create an authoritative audit event containing the requester, timestamp, Skill and model version, relevant input or content identifiers, generated output, review status, and retention classification. Audit evidence cannot depend on whether the model remembers or chooses to invoke a logging instruction.
Options C, D, and E describe reusable generation behavior that appropriately belongs within the approved Skill: house style, the standardized disclaimer, and the prohibited-language policy. The application may still validate their presence after generation, but the Skill remains the primary reusable content package.
The correct architecture separates behavioral guidance from deterministic enforcement. Skills supply domain instructions and templates; the application enforces identity, authorization, audit retention, data access, output validation, and consequential-action controls.
Study Guide references/topics: Skills versus application controls; authentication; authorization; compliance logging; deterministic guardrails; policy enforcement boundaries.
NEW QUESTION # 13
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?
Answer: B
Explanation:
The network-boundary requirement is a mandatory architectural constraint; therefore, Option D must be resolved before evaluating operational savings. Managed infrastructure can reduce responsibility for agent loops, sandboxes, session state, recovery, and orchestration, but those advantages are immaterial if financial data leaves the approved boundary. Anthropic describes Claude Managed Agents as a hosted agent harness and provides configurable data-residency controls . The architect must still validate inference location, session persistence, encryption, subprocessors, credential handling, auditability, and deletion behavior against the organization's exact security policy. Options A, B, and C affect migration effort or economics, but they cannot override a non-negotiable data-governance requirement.
Study Guide references/topics: Architectural constraints; managed versus self-hosted agents; data boundaries; residency; security-gated decision-making.
NEW QUESTION # 14
A Claude architect is implementing safety controls for a customer-facing advice assistant that must never provide regulated investment recommendations.
Which two guardrail implementations most directly enforce this constraint? (Select two.)
Answer: C,D
Explanation:
The required control is best implemented through layered prevention. The system prompt should explicitly classify personalized investment recommendations as out of scope, instruct Claude not to recommend particular securities or transactions, and provide standardized refusal language. Fixed refusal behavior reduces ambiguity and gives the model a clear alternative response when users request prohibited advice or attempt to reframe it indirectly.
An output classifier supplies an independent enforcement layer after generation but before delivery. It should detect prohibited recommendation language, individualized buy-or-sell instructions, portfolio allocations, and equivalent regulated content. A detected violation must block or replace the response rather than merely record it. This protects against prompt circumvention, unexpected phrasing, and occasional model noncompliance.
Increasing temperature makes responses less predictable and weakens control reliability. Session-length limits regulate volume, not content. SIEM logging is valuable for monitoring, investigation, and compliance evidence, but it is detective rather than preventative: the prohibited recommendation may already have reached the customer.
The completed design should evaluate both layers using adversarial prompts, paraphrases, multi-turn escalation, and classifier false-negative testing.
Study Guide references/topics: [Mitigating jailbreaks and prompt injections](https://docs.anthropic.com/en
/docs/test-and-evaluate/strengthen-guardrails/mitigate-jailbreaks); layered guardrails; explicit scope boundaries; standardized refusals; output classification; pre-delivery enforcement.
NEW QUESTION # 15
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