Anthropic CCA-F

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Anthropic CCA-F Exam Syllabus Topics:

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

Question #1
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. The API returned cached responses.
B. Large language models are probabilistic.
C. Claude is malfunctioning.
D. Retrieval failed.

Question #2
You are building a multi-agent research system using the Claude Agent SDK. A coordinator agent delegates to specialized subagents: one searches the web, one analyzes documents, one synthesizes findings, and one generates reports. The system researches topics and produces comprehensive, cited reports.
A user is expanding the research system beyond its single web search agent by adding specialized data sources. They add a financial API agent that returns structured JSON with revenue, margins, and growth rates; a news monitoring agent that returns prose summaries of recent developments; and a patent analysis agent that returns structured lists of technology areas. The synthesis agent combines these into executive briefings. Currently, it converts everything to bullet points, causing financial comparisons to lose tabular clarity and news summaries to lose narrative flow. What change would most improve briefing quality?

A. Standardize all subagent outputs to JSON with fields for claim, evidence, source, and confidence
B. Standardize all subagent outputs to prose summaries with inline citations
C. Add a format conversion layer between subagents and synthesis that transforms all outputs to a common intermediate representation
D. Update the synthesis agent to render each content type appropriately - financial data as tables, news as prose

Question #3
A company is building its first production Claude application. Which principle should guide the initial deployment?

A. Start with a simple design and iteratively evaluate improvements.
B. Maximize prompt complexity immediately.
C. Disable monitoring to reduce costs.
D. Optimize only for response speed.

Question #4
An engineering team notices that Claude occasionally provides answers beyond the company's internal policy documents. They want responses to rely only on approved documentation whenever possible. Which solution is MOST appropriate?

A. Shorten every prompt
B. Increase temperature to 1.0
C. Use Retrieval-Augmented Generation (RAG)
D. Disable system prompts

Question #5
Your order management system requires tools for three distinct operations: issuing refunds (requires amount and reason), canceling orders (requires reason), and requesting reshipments (requires shipping address). Each operation shares an order_id parameter but has different additional requirements. You notice during testing that with your current unified tool design, the agent frequently omits required parameters or includes irrelevant ones. What design change will most effectively improve parameter accuracy?

A. Keep one unified tool with a nested operation_details object parameter whose internal structure varies by operation type, documented in the tool description.
B. Keep one unified tool with all parameters marked optional, but add detailed few-shot examples in the system prompt showing correct parameter combinations for each operation type.
C. Keep one unified tool but add JSON Schema if-then-else conditionals to enforce that parameters like amount are required only when the operation type is "refund".
D. Split into three separate tools (issue_refund, cancel_order, request_reshipment), each defining only the parameters required for that specific operation.

Solutions: