자료의 품질이 걱정되신다면 확인 방법은 간단합니다. KoreaDumps에서 CCAR-F 무료 샘플을 내려받아 Anthropic Claude Certified Architect - Foundations 대비 문제의 일부를 직접 살펴보시기 바랍니다.

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Anthropic Claude Certified Architect - Foundations에 대해 알아야 할 모든 것

최신 Claude Certified Architect CCAR-F 무료샘플문제

문제 #1

You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline. The system runs automated code reviews, generates test cases, and provides feedback on pull requests. You need to design prompts that provide actionable feedback and minimize false positives.
Your automated code review is missing genuine bugs in pull requests. Investigation reveals that your review prompt includes the instruction: "Only flag critical issues that would definitely cause production failures. Ignore minor concerns and anything you are uncertain about." Developers confirm that some missed bugs are genuine logic errors that the model investigated but chose not to report. The team requires the review output to remain structured, with each finding tagged with metadata, and actionable.
Which prompt change both removes the cause of the suppressed findings and preserves structured, tagged output for downstream filtering?

A. Instruct the model to report all findings with confidence and severity tags, deferring filtering to a downstream step.
B. Add a second review pass that rereads the diff using the same prompt, looking for anything the first pass may have missed.
C. Remove all severity-related instructions from the prompt and let the model use its default judgment about what to report.
D. Enable extended thinking and instruct the model to reason step by step about every code change before producing its review.

문제 #2

A developer wants Claude to explain every reasoning step internally before answering. Why might this request be inappropriate?

A. Claude requires GPU acceleration.
B. Temperature prevents explanations.
C. Internal reasoning should not be relied upon as an application feature.
D. JSON cannot contain reasoning.

문제 #3

Production reviews reveal inconsistent handling of uncertainty in final reports. Sometimes conflicting subagent findings are synthesized into a single confident statement (losing nuance), while other times reports over-hedge with excessive qualifications (becoming unhelpful). When the web search agent returns "industry analysts estimate $50B market size (methodology varies)" and the document analysis agent returns "peer-reviewed study estimates $35B (±$7B, 95% CI)," the coordinator either picks one arbitrarily or produces vague statements like "the market may be
$35B-$50B depending on factors." What systematic approach best addresses this?

A. Configure subagents to only report findings meeting a high-confidence threshold, filtering uncertain information before it reaches the coordinator.
B. Instruct the synthesis agent to structure reports with explicit sections distinguishing well- established findings from contested ones, preserving original source characterizations and methodological context.
C. Add a verification subagent that cross-references findings across sources, only passing claims to synthesis that are corroborated by at least two independent sources.
D. Implement a confidence calibration layer that normalizes subagent uncertainty expressions to standardized probability scores (0.0-1.0), then weight-average findings by their calibrated confidence.

문제 #4

You are using Claude Code to accelerate software development. Your team uses it for code generation, refactoring, debugging, and documentation. You need to integrate it into your development workflow with custom slash commands, CLAUDE.md configurations, and understand when to use plan mode vs direct execution.
A critical bug is affecting production users. Error logs show exceptions in the OrderProcessing module with a clear stack trace pointing to a specific function. You haven't worked with this module before. What's the most effective approach?

A. Enter plan mode to explore the module's architecture and dependencies before attempting any fixes.
B. Use direct execution to examine the stack trace, read the relevant code, and implement a fix once you identify the root cause.
C. Use plan mode to analyze the error in context of the module's design, enumerate potential root causes, and prioritize fixes systematically.
D. Start with direct execution to gather initial information, then switch to plan mode to design a comprehensive solution before implementing any changes.

문제 #5

The web search agent has gathered several relevant sources for a research topic. The document analysis agent now needs to examine these sources. How does information typically flow between these two specialized subagents?

A. The web search agent directly invokes the document analysis agent, passing the discovered sources as parameters.
B. Both agents access a shared memory store where the web search agent writes findings and the document analysis agent reads them.
C. The agents communicate through an event-driven message queue, with the document analysis agent subscribing to web search completion events.
D. The coordinator agent receives the web search agent's output and includes relevant findings in the prompt when invoking the document analysis agent.

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