Anthropic Claude Certified Architect Foundations (CCA-F) : CCA-F

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions:

1. Your document extraction tool uses ML models to extract invoice fields (vendor, amount, date).
The models return confidence scores (0.0-1.0) for each extracted field. In production, you observe: (1) the agent proceeds with low-confidence extractions that are incorrect 23% of the time, and (2) the agent requests unnecessary human review for 31% of extractions that were actually correct. How should you restructure the tool's output?

A) Return fields with confidence scores, plus a request_review boolean computed using your tested confidence thresholds, along with a review_reasons array explaining which fields triggered review.
B) Return fields organized into verified and needs_verification objects based on confidence thresholds.
C) Compute an aggregate extraction_quality score across all fields and return it alongside the extracted values. Include a text summary describing the overall extraction reliability.
D) Return fields with their raw confidence scores and add detailed few-shot examples to your system prompt demonstrating how to interpret different confidence ranges and when to request human review.

2. A retail organization observes that Claude occasionally gives different wording when summarizing identical customer reviews. The summaries remain accurate. What is the MOST likely explanation?

A) Claude is malfunctioning.
B) The API returned cached responses.
C) Retrieval failed.
D) Large language models are probabilistic.

3. You've configured the system so that all four subagents have access to the complete set of
18 tools. During testing, agents frequently call tools outside their specialization - the synthesis agent attempts web searches, and the report generator tries to analyze documents. What is the primary cause of this poor tool selection behavior?

A) The agents' role descriptions in their system prompts conflict with having access to tools outside that role.
B) The tool definitions consume too much context window space, leaving insufficient room for task content.
C) Choosing from 18 tools instead of 4-5 relevant ones increases decision complexity beyond reliable selection thresholds.
D) The coordinator cannot track which capabilities each subagent has, leading to misrouted tasks.

4. Why is evaluation important after deploying a Claude application?

A) It increases context size.
B) It measures response quality against defined objectives.
C) It permanently changes model parameters.
D) It reduces network latency.

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

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

Solutions: