Updated: Oct 12, 2026
No. of Questions: 130 Questions & Answers with Testing Engine
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| Certification Vendor: | Anthropic |
|---|---|
| Exam Name: | Claude Certified Architect – Professional (CCAR-P) Exam |
| Exam Number: | CCAR-P |
| Exam Duration: | 120 minutes |
| Exam Format: | Scenario-based, Multiple Choice, Multiple Response |
| Exam Price: | USD $175 |
| Certificate Validity Period: | 12 months from award date |
| Related Certifications: | Claude Certified Architect – Foundations (CCAR-F) Claude Certified Associate – Foundations (CCAO-F) Claude Certified Developer – Foundations (CCDV-F) |
| Real Exam Qty: | 63 |
| Passing Score: | 720 (on a scale of 100–1000) |
| Available Languages: | English |
| Recommended Training: | Anthropic Partner Academy Free Training |
| Exam Registration: | Anthropic Partner Academy Registration Pearson VUE Exam Scheduling |
| Sample Questions: | Anthropic CCAR-P Sample Questions |
| Exam Way: | Online proctored (Pearson VUE OnVUE) or in-person at Pearson VUE test center |
| Pre Condition: | No mandatory prerequisites; Claude Certified Architect – Foundations (CCAR-F) or equivalent experience strongly recommended. Recommended: 3+ years in systems architecture / platform engineering plus 6+ months hands-on Claude/LLM production experience. |
| Official Syllabus URL: | https://partners.anthropic.com/certifications |
| Section | Weight | Objectives |
|---|---|---|
| Governance, Safety & Risk Management | 14% | - Ensure regulatory compliance (GDPR, HIPAA, etc.) - Implement guardrails and safety controls - Address ethical AI considerations and bias mitigation - Manage data privacy and security compliance |
| Developer Productivity & Operational Enablement | 7% | - Support debugging, monitoring, and operational resolution - Improve developer workflows with AI-assisted tooling - Configure Claude tools and environments for teams |
| Integration | 19% | - Implement Model Context Protocol (MCP) integrations - Integrate Claude with enterprise systems, APIs, and tools - Design authentication, authorization, and observability - Integrate with data pipelines and RAG systems |
| Stakeholder Communication & Lifecycle Management | 14% | - Communicate architectural decisions and trade-offs - Manage stakeholder feedback and expectation alignment - Conduct structured discovery and requirement gathering - Document architectures and support full lifecycle phases |
| Claude Models, Prompting & Context Engineering | 13% | - Design system prompts, templates, and guardrails - Select appropriate Claude models based on trade-offs - Mitigate prompt injection, leaks, and jailbreak risks - Apply context engineering and context management techniques |
| Solution Design & Architecture | 17% | - Design multi-agent systems and orchestration strategies - Translate business problems into Claude-based AI solutions - Align solutions to business value pillars - Select architectural patterns: workflow, agentic, augmented LLM - Design end-to-end architectures and feedback loops |
| Evaluation, Testing & Optimization | 16% | - Test accuracy, reliability, latency, and cost - Implement iterative improvement pipelines - Define evaluation metrics and success criteria - Optimize performance, prompting, and model selection |
An architect is reviewing a set of architecture documentation packages before handing off a Claude-based pipeline to an implementation team.
Which two characteristics indicate that a documentation package is sufficient to support implementation without ongoing architect involvement? (Select two.)
Correct Answer: A,B 🗳️
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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.)
Correct Answer: B,C 🗳️
Explanation: Only visible for Pass4SureQuiz members. You can sign-up / login (it's free).
You are a platform architect designing an internal Claude-based assistant that serves both finance analysts and external auditors. Each population must access only documents permitted by its role.
Where should role-based access control be enforced in the pipeline?
Correct Answer: B 🗳️
Explanation: Only visible for Pass4SureQuiz members. You can sign-up / login (it's free).
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?
Correct Answer: B 🗳️
Explanation: Only visible for Pass4SureQuiz members. You can sign-up / login (it's free).
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."
Correct Answer:

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
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