Free Claude Certified Architect - Professional (CCAR-P) Practice Questions

Sample CCAR-P Practice Questions

Browse all 10 free Claude Certified Architect - Professional practice questions below.

1. A retail bank is automating new-account onboarding triage. Every application moves through the same three stages: extract fields from the ID document, validate them against the application form, and flag discrepancies for a human reviewer. Compliance requires that each stage's output be independently inspectable, and the stage sequence has not changed in four years. Which architecture best fits these constraints?

   • A prompt-chained workflow with one model call per stage and programmatic validation gates between the stages.
   • An orchestrator agent that decomposes each application into subtasks and delegates them to worker agents at run time.
   • A single model call with a comprehensive prompt covering extraction, validation, and discrepancy flagging together.
   • A routing step that classifies each application and dispatches it to one of several specialized handler prompts.

2. An e-commerce support agent has grown to more than 40 tools covering orders, refunds, inventory, and shipping. Tool-selection accuracy has fallen, input costs have risen, and prompt cache hit rates drop after each tool addition. The team must keep all capabilities available. Which TWO changes most directly address the degradation? (Select TWO)

   • Consolidate overlapping tools and rewrite each description to state exactly when it should be invoked.
   • Set tool_choice to any so the agent always commits to some tool instead of answering from stale context.
   • Move the full tool list into the system prompt so it sits in a stable position for caching.
   • Raise max_tokens on every request so the model has more room to reason before committing to a tool call.
   • Adopt the tool search tool and mark rarely used tools defer_loading so schemas load only when relevant.

3. A logistics platform classifies 30 million short carrier status messages per day into 12 fixed delivery states. Accuracy on a labeled sample is already 97% with a small model, the p95 latency budget is 500 ms, and finance has capped monthly model spend. Which model choice fits these constraints?

   • Claude Fable 5.1, because always-on deep reasoning maximizes per-message accuracy.
   • Claude Haiku 5.5 at low effort, validated against the labeled sample before rollout.
   • Claude Sonnet 5.5, since its stronger reasoning adds accuracy headroom.
   • Claude Opus 5.5, to standardize on one model across all company workloads.

4. A hospital network's Claude feature summarizes patient intake forms for clinicians. Leadership wants to expand it to three more clinics but first needs evidence that the summaries are reliable. Intake forms vary widely in quality and specialty across sites. What is the strongest form of evidence to gather before expansion?

   • Scores from a held-out set of real de-identified intake forms spanning specialties, graded by clinicians against a written rubric.
   • The model's published scores on standard medical benchmarks and general reasoning suites, compared against the tiers the team considered.
   • Average clinician star ratings collected from the pilot clinic's daily use of the feature over the full quarter since launch.
   • A staged rollout to one additional clinic with close monitoring of complaints and correction requests during the first month.

5. A financial-services chatbot built on Claude occasionally echoes a customer's full account number back in replies, which the bank's data-handling policy forbids in any channel. The team needs the strongest control to stop account numbers from reaching customers. Where should that control live?

   • In a deterministic output filter that scans and masks account-number patterns before any reply is displayed.
   • In the retrieval layer, by excluding account numbers from every document indexed for the assistant's knowledge base.
   • In a fine-tuned model variant trained on historical transcripts in which account numbers were consistently masked.
   • In the system prompt, as an explicit rule that account numbers must be masked or truncated in every customer-facing reply.

6. A freight forwarder processes 40,000 customs declarations every night. For roughly 92 percent of documents, the same nine fields extract cleanly in a single structured-output call; the remainder are degraded scans that need a tariff-code lookup and a second extraction pass. Finance has capped per-document cost, and operations requires predictable nightly throughput. Which architecture best fits these constraints?

   • Route every declaration through an autonomous agent loop with lookup tools so clean and degraded documents follow one adaptive path
   • Run a fixed extraction pipeline with a confidence gate that routes only low-confidence documents into a lookup-and-reextract branch
   • Use an orchestrator agent that spawns a specialized extraction sub-agent per field so all nine fields are pulled independently in parallel
   • Process each document in one structured-output call and iterate on the prompt until degraded scans reach parity with clean-scan accuracy

7. A biotech startup's internal research assistant needs to call one endpoint of the company's lab information system to fetch assay results. No other AI client exists or is planned this quarter, the API is stable and versioned, and the two-engineer team must ship in three weeks. Which integration mechanism matches this scope and timeline?

   • Deploy a standalone MCP server wrapping the lab system so the capability becomes discoverable by future Claude clients across the company
   • Front the lab system with its own agent and have the assistant delegate assay queries to it over an agent-to-agent interface
   • Build a thin internal gateway service that translates the assistant's natural-language requests into structured lab-system API calls
   • Define a single tool against the existing REST endpoint and invoke it through Messages API tool use from the assistant

8. An insurer classifies incoming claims with a prompt carrying about 6,000 tokens of stable guidelines, taxonomy, and worked examples, followed by a short variable claim description. Volume is roughly 900,000 classifications per week, results feed a nightly job rather than a live user, and accuracy must not regress. Which TWO changes cut cost the most while preserving accuracy? (Select TWO)

   • Reorder the prompt so the variable claim description comes first and the stable guidelines follow at the end of each request
   • Split the taxonomy across several smaller sequential calls so each individual request carries a lighter context load
   • Mark the stable guideline-and-example block with a cache breakpoint so repeated requests read it at the reduced cached-token rate
   • Submit the classifications through the Message Batches API, which halves token pricing for asynchronous workloads
   • Move the workload to a larger model tier so the worked examples can be dropped from the prompt while holding accuracy

9. A home-goods retailer has written a new prompt version for its product-description generator. The team holds 400 expert-labeled examples with a scoring rubric, and leadership wants a go or no-go decision this week, before any customer traffic sees the new version. What is the soundest way to decide between the two prompts?

   • Have the generating model review each pair of outputs and record which version it judges stronger for every item
   • Release the new version behind a feature flag to full traffic and compare this week's engagement metrics with last week's
   • Launch a four-week production A/B test and use the labeled set only as a tie-breaker if the test proves inconclusive
   • Score both prompt versions against the held-out labeled set using the fixed rubric and compare the results side by side

10. A wealth-management firm uses Claude to draft investment-suitability memos that advisers act on directly with clients. Compliance is worried about a single failure mode: a fabricated figure in a memo driving a client decision. Which control most directly reduces that risk?

    • Require the model to attach a source citation beside every figure it includes in each generated memo
    • Require adviser sign-off checking each figure against the cited source records before client use
    • Set temperature to zero so each memo is generated deterministically from the same underlying inputs
    • Add a standing notice to memos stating that figures should be independently verified before reliance