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Anthropic CCAR-P Exam Syllabus Topics:

SectionObjectives
Topic 1: Enterprise Integration and Production- Cost, latency, reliability, and operational design
- Enterprise integration architecture and production readiness
Topic 2: Solution Design- Claude platform and solution architecture
- Model, architecture, context, and deployment strategy selection
Topic 3: Evaluation and Optimization- Evaluation design and acceptance criteria
- Model and architecture optimization
Topic 4: Stakeholder Engagement and Solution Lifecycle- Solution lifecycle, handoff, adoption, and operational enablement
- Stakeholder discovery and architectural trade-off communication
Topic 5: Governance, Safety, and Risk- Safety controls and fail-closed system design
- Security, compliance, risk management, and governance

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Anthropic Claude Certified Architect - Professional Sample Questions (Q97-Q102):

NEW QUESTION # 97
You are building an ethics review checklist for deployments supported by artificial intelligence (AI). Which two checks belong on the list? (Select two.) Each correct answer presents a complete solution.

Answer: C,D

Explanation:
High-impact AI-supported decisions must retain clearly assigned human accountability. Claude may provide recommendations, classifications, or generated content, but responsibility for consequential outcomes cannot be transferred to the model. An ethics review should also investigate whether outputs make unsupported generalizations about individuals or groups, because such behavior can produce discriminatory, misleading, or harmful outcomes. Therefore, B and E directly address ethical accountability and fairness. Licensing in option A is an important legal and procurement concern, but it is not the strongest ethics-focused control presented.
Latency and throughput in option D are operational performance requirements. Option C is inappropriate because ethics risks are not limited to outputs above a confidence threshold; confidence values may also be poorly calibrated and do not prove that an output is fair, accurate, or ethically acceptable.


NEW QUESTION # 98
You are compiling a diagnostic toolkit for Claude Code operational issues.
Which two diagnostic actions belong in the toolkit? (Select two.)
Each correct answer presents a complete solution.

Answer: B,C

Explanation:
A minimal reproduction and MCP status inspection are foundational diagnostic actions because they produce direct, interpretable evidence. A minimal reproduction removes unrelated prompts, tools, settings, hooks, and repository state while changing one variable at a time. This determines whether the failure follows a particular configuration, server, command, model request, or project artifact. It also creates a reproducible evidence package if escalation later becomes necessary.
MCP inspection addresses a common Claude Code failure domain. `claude mcp list` displays configured servers and their health states, including connected, authentication-required, pending-approval, and failed-to- connect conditions. `claude mcp get < name > ` provides server-specific details, while `/mcp` exposes status within an interactive session. These checks distinguish model behavior from transport, authentication, configuration, and workspace-trust failures.
Increasing temperature reduces repeatability and introduces additional variation, making root-cause isolation more difficult. Filing a support ticket before collecting local evidence reverses the appropriate diagnostic sequence. An immediate rollback may eventually be used as a controlled version comparison, but it changes the environment before a baseline has been captured and is therefore not a primary toolkit action.
Study Guide references/topics: [Managing and diagnosing MCP servers](https://docs.anthropic.com/en/docs
/claude-code/mcp); minimal reproducible cases; controlled-variable troubleshooting; authentication and connection-state diagnostics.


NEW QUESTION # 99
You are compiling guardrail tactics for a customer-facing assistant.
Which two tactics belong on the guardrail list?
Each correct answer presents a complete solution.

Answer: C,E

Explanation:
Option C introduces a deterministic validation boundary between probabilistic model output and downstream execution. Structured validation can reject missing fields, invalid types, unauthorized actions, malformed arguments, and values outside approved enumerations before any tool or business process acts on the response. Anthropic recommends Structured Outputs when guaranteed schema conformance is required.
Increase Output Consistency
Option D implements defense in depth. Prompt-level instructions establish intended behavior, while runtime classifiers, content filters, policy engines, output validators, tool permissions, and human confirmation gates provide controls outside the model. Anthropic's guardrail guidance recommends combining safeguards rather than depending on one mechanism. Mitigate Jailbreaks and Prompt Injections Option A creates a bypass mechanism that adversaries may discover or imitate. Option B may alter output variability but is not a security boundary and cannot guarantee policy compliance. Option E places complete reliance on a system prompt, which remains vulnerable to ambiguity, conflicting inputs, model errors, and indirect prompt injection.
Guardrails should be risk-based, independently enforceable where possible, observable, tested against adversarial cases, and proportional to the consequences of downstream actions.
Study Guide references/topics: Layered guardrails; structured validation; runtime content checks; prompt injection; deterministic enforcement; defense in depth.


NEW QUESTION # 100
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 # 101
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: C,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 # 102
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