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Anthropic CCAR-P Exam Syllabus Topics:

Anthropic Claude Certified Architect - Professional Sample Questions:

1. You are identifying the highest-impact optimization for a deployment whose token cost is dominated by a long, repeated system prompt and a large retrieved context per request.
Which optimization most directly targets the dominant cost driver?

A) Add additional repeated content to the system prompt to give the model more guidance.
B) Move the long, repeated system prompt into a cacheable prefix and trim retrieved context to the spans relevant to each query.
C) Increase retrieval depth on every request to maximize recall, worsening the dominant cost driver by adding more retrieved tokens per request rather than reducing them.
D) Switch every request to the heaviest available model to maximize output quality, accepting that higher per-request inference cost compounds rather than addresses the dominant cost driver.

2. You are classifying chunking strategies by the corpus type each is best suited to.
For each chunking strategy, select the appropriate corpus type: "Long Structured Documents,"
"Heterogeneous Short Records," or "Code or Hierarchical Specifications."

3. You are diagnosing a Claude Code session whose subagent uses 50,000 tokens of context before the engineer types a single message.
Which root cause is most likely?

A) Many MCP servers are configured, each contributing tool definitions to the context budget; Tool Search is not enabled, so all definitions load upfront.
B) The model has internal personal preferences or default behaviors that silently consume large portions of context budget before any user message is processed, independent of tool configuration.
C) The developer's keyboard layout or input-method configuration is the cause of the elevated context consumption, introducing extra tokens before the engineer types any message.
D) The font rendering or display-scaling settings of the IDE are converting visual output into additional context tokens, causing the high pre-session context consumption.

4. You are reviewing instrumentation in a multi-agent system.
Which two findings constitute valid observability gaps in the instrumentation? (Select two.) Each correct answer presents a complete solution.

A) Request-scoped correlation identifiers do not propagate across agent and tool calls.
B) Trace spans for each agent step are exported to the shared distributed-tracing backend.
C) Tool-call payloads and outcomes are recorded with redaction applied to known sensitive fields.
D) Model identity and version on each turn are not recorded with the turn artifacts.
E) Latency and token usage on every span are emitted to the central metrics pipeline.

5. You are selecting a pattern for a compliance Q & A assistant that must answer policy questions with citations to the authoritative internal source set. Latency, cost, and audit predictability are prioritized.
Which pattern is the best fit?

A) Multi-agent orchestration with a planner, researcher, and writer agent for every query.
B) A pure agent loop with open web-browsing tools to surface the most current policy information, without constraining retrieval to the authoritative internal corpus.
C) Augmented LLM with retrieval-augmented generation over the indexed authoritative corpus and citation rendering on each answer.
D) A static prompt with the entire policy corpus concatenated into every request.

Solutions: