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

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Anthropic CCA-F Exam Syllabus Topics:

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

Question #1
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. The coordinator cannot track which capabilities each subagent has, leading to misrouted tasks.
D. Choosing from 18 tools instead of 4-5 relevant ones increases decision complexity beyond reliable selection thresholds.

Question #2
After 30+ turns, your conversational assistant shows noticeably slower responses and occasionally produces less coherent outputs. Investigation reveals: (1) average conversations reach 50,000 tokens by turn 35, (2) production logs show 94% of user messages only reference the previous 3-5 exchanges, (3) the 6% of queries referencing earlier context typically ask about information the user could easily re-state. Your goal is to improve response speed and quality while maintaining good user experience. What's the most effective approach?

A. Implement a summarization layer that progressively compresses older conversation turns into a running summary while keeping the most recent 5-6 turns verbatim, maintaining full historical context in condensed form.
B. Enable prompt caching and continue sending the complete conversation history, using cached prefixes to reduce per-request costs while preserving all context.
C. Build a retrieval system that stores all conversation turns and uses semantic search to pull in relevant historical context only when the current query appears to reference past information.
D. Implement a sliding window keeping only the system prompt and last 8-10 turns. When users reference earlier context, acknowledge the limitation and ask them to re-state the relevant information.

Question #3
A financial services company plans to integrate Claude into an internal document analysis platform. The architects want to minimize exposure of confidential client information while maintaining high-quality responses. Which approach BEST aligns with Anthropic's recommended architecture?

A. Send every document without preprocessing to maximize context.
B. Store every prompt permanently for auditing.
C. Replace Claude with a smaller local model regardless of task complexity.
D. Remove unnecessary sensitive information before sending prompts whenever possible.

Question #4
Your content curation agent discovers articles, analyzes each for relevance, then adds selected articles to themed collections. With separate discover_articles(topic), analyze_article(id), and add_to_collection(article_id, collection_id) tools, you observe 18+ sequential tool calls per request, causing latency issues. The agent must make editorial judgments about which articles fit a collection's theme - this requires seeing all candidates with their analysis scores simultaneously to select a cohesive set. What tool composition best addresses efficiency while preserving editorial judgment?

A. Keep all tools separate but implement response caching for analyze_article calls.
B. Add a preview_curation(topic, collection_id) tool that shows what would be added based on predefined rules, with an approve_curation() tool to confirm.
C. Create a discover_and_analyze(topic) composite tool that returns all candidates with their analysis scores, keeping add_to_collection separate for selective calls.
D. Create a curate_collection(topic, collection_id) tool that handles discovery, analysis, and selection internally using configurable quality thresholds.

Question #5
Your multi-agent research pipeline crashed after processing12 of 28 documents. The web search agent had identified relevant sources, the document analyzer had partially completed extraction, and the synthesizer had begun pattern identification. You need to resume processing without repeating work or losing fidelity of prior findings. What state management approach best balances information fidelity with context efficiency when restoring agent state?

A. Have each agent maintain its own persistent state file and reload it independently at the start of each session.
B. Have each agent persist a structured export to a known location. On resume, the coordinator loads the manifest and injects relevant state into agent prompts.
C. Index all agent outputs in a shared vector store. When resuming, each agent queries the store using semantic search to retrieve relevant prior findings.
D. Persist the coordinator's conversation log containing all task delegations and responses, providing this to agents when resuming.

Solutions: