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Anthropic CCA-F Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Context Management & Reliability15%- Long-context optimization
  • 1. Reliability and retry strategies
    • 2. Context window management
      Topic 2: Agentic Architecture & Orchestration27%- System orchestration patterns
      • 1. Hub-and-spoke agent systems
        • 2. Task decomposition strategies
          - Agentic loop design and execution lifecycle
          • 1. Multi-agent coordination and delegation patterns
            • 2. Tool use decision flow (tool_use vs end_turn)
              Topic 3: Claude Code Workflows & Configuration20%- Claude Code operational patterns
              • 1. CI/CD and workflow integration
                • 2. Plan mode vs execution mode
                  Topic 4: Prompt Engineering & Structured Output20%- Reliable structured generation
                  • 1. Schema-guided outputs
                    • 2. Prompt patterns for agents
                      Topic 5: Tool Design & MCP Integration18%- Model Context Protocol (MCP)
                      • 1. Tool schema design
                        • 2. MCP client/server integration patterns

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                          Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q69-Q74):

                          NEW QUESTION # 69
                          When implementing a hub-and-spoke multi-agent architecture using the Claude Agent SDK, which of the following statements about subagent spawning and execution are correct? Choose 2 correct answers.

                          Answer: A,D

                          Explanation:
                          To spawn subagents, the coordinator must be configured with 'Task' in its allowedTools. Furthermore, emitting multiple Task tool calls in a single response allows the subagents to execute their tasks in parallel. Subagents do not automatically inherit conversation history, and forcing sequential spawning is inefficient.


                          NEW QUESTION # 70
                          During a billing dispute resolution, your agent successfully retrieves customer info via get_customer and order details via lookup_order, but when attempting to call process_refund, the tool returns a timeout error. The agent has enough information to explain the charges and verify refund eligibility, but cannot actually process the refund due to the backend failure. What approach best balances first-contact resolution with appropriate error handling?

                          Answer: C

                          Explanation:
                          The agent should use the information it already has to resolve as much of the customer's issue as possible, while being transparent that the refund could not be processed because of a backend timeout. Offering escalation or a later retry preserves trust and supports first-contact resolution without falsely claiming the action was completed.


                          NEW QUESTION # 71
                          Which statement BEST describes Retrieval-Augmented Generation?

                          Answer: B

                          Explanation:
                          RAG retrieves relevant documents at inference time and includes them within the prompt. The model itself is unchanged, allowing organizations to incorporate current enterprise knowledge without retraining foundation models.


                          NEW QUESTION # 72
                          A quicktechie.com team wants to run a nightly code quality audit across the entire codebase using Claude Code to reduce API costs.
                          Which approach is most cost-effective and architecturally sound?

                          Answer: B

                          Explanation:
                          The Message Batches API processes requests within a 24-hour window and offers a 50% cost savings compared to synchronous requests. It is ideal for latency-tolerant, non-urgent workloads like overnight technical debt audits.


                          NEW QUESTION # 73
                          A developer is using a multi-agent system to analyze a massive legacy codebase. The coordinator agent is running out of context window space because the search tool returns verbose file contents and exploration noise. What is the best pattern to mitigate this context degradation?

                          Answer: C

                          Explanation:
                          Subagent delegation is a core mitigation for context degradation. By delegating verbose exploration tasks to subagents, the subagent's isolated context absorbs the exploration noise, and only the clean, synthesized results are returned to the coordinator.


                          NEW QUESTION # 74
                          ......

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