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Anthropic CCAR-P Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Enterprise Integration and Production | - Enterprise integration architecture and production readiness - Cost, latency, reliability, and operational design |
| Topic 2: Evaluation and Optimization | - Evaluation design and acceptance criteria - Model and architecture optimization |
| Topic 3: Solution Design | - Model, architecture, context, and deployment strategy selection - Claude platform and solution architecture |
| Topic 4: Governance, Safety, and Risk | - Safety controls and fail-closed system design - Security, compliance, risk management, and governance |
| Topic 5: Stakeholder Engagement and Solution Lifecycle | - Solution lifecycle, handoff, adoption, and operational enablement - Stakeholder discovery and architectural trade-off communication |
Anthropic Claude Certified Architect - Professional Sample Questions:
1. You are a solution architect designing a Claude-based assistant with access to 60 internal tools across multiple business domains. Loading every tool definition on every request increases token usage and time to first response.
Which design pattern best addresses this issue without sacrificing capability breadth?
A) Apply progressive tool discovery so a curated initial subset is exposed and additional tools are loaded on demand based on the task.
B) Increase the maximum context length and load all 60 tool definitions on every request, accepting the higher token cost and latency as necessary for full capability.
C) Hard-code a fixed set of five tools per request to reduce token usage, regardless of whether those tools are relevant to the current task.
D) Use a separate model call to summarize all 60 tool definitions before each user turn.
2. A Claude architect at a health services organization is defining evaluation metrics for a clinical-summary pipeline. The pipeline must remain within a per-query cost ceiling and must never surface patient data to unauthorized roles.
Which two metrics directly address these requirements? (Select two.)
A) BLEU score computed against a human-annotated reference summary set
B) Response latency at the 95th percentile across a one-week sample window
C) Role-based access-control enforcement rate measured on a red-team dataset
D) Throughput measured as successful requests processed per minute
E) Per-query token cost measured against the defined cost ceiling
3. You are listing characteristics of strong architectural-decision communication.
Which two characteristics belong on the list? (Select two.)
Each correct answer presents a complete solution.
A) Use of a consistent template across the team to standardize the visual presentation of decisions.
B) Alternatives considered along with the criteria that were used to evaluate each alternative.
C) Ownership and review cadence for revisiting the decision when conditions or assumptions change.
D) Omission of rejected alternatives to keep the decision document focused and concise for readers.
E) Distribution to a standing review forum with mandatory attendance from senior engineering leaders.
4. A Claude architect is designing a HIPAA-compliant pipeline that processes patient records.
Which two design decisions directly support HIPAA compliance requirements? (Select two.)
A) Setting max_tokens to a low value to minimize the volume of text generated per request.
B) Using streaming responses to reduce perceived latency for clinical users.
C) Ensuring patient data is never included in training feedback loops sent to the model provider without a BAA in place.
D) Enforcing role-based access controls so that PHI is retrievable only by authorized personnel.
E) Selecting the highest-capability Claude model to maximize diagnostic accuracy.
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) Route straightforward query types to a smaller, faster Claude model and reserve the full model for complex cases.
B) Expand the system prompt to include additional few-shot examples on every request.
C) Enable prompt caching on the static system-prompt prefix to reduce billable input tokens on repeated calls.
D) Increase max_tokens to reduce the frequency of truncated responses requiring follow-up calls.
E) Add a retrieval step that fetches the full source corpus into the context window before generation.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C,E | Question # 3 Answer: B,C | Question # 4 Answer: C,D | Question # 5 Answer: A,C |
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