CCAR-P Practice Test 2 — 30 Questions

Question 1

A support agent built on Claude must decide whether a customer request is a billing issue, a technical issue, or a general inquiry before routing it. The categories are fixed and mutually exclusive, and the routing decision must be fast and cheap. Which approach is most appropriate?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Use a single Claude call with a constrained output format such as a tool definition or structured JSON that returns exactly one category label.. Fixed, mutually exclusive categories with strict latency and cost goals are best handled by a single Claude call that constrains output to one of the allowed labels. Using a tool definition or JSON schema with an enum removes ambiguity and avoids the overhead of multi-agent orchestration or a separate fine-tuned model.

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Fine-tune a separate model on historical tickets and deploy it alongside the Claude agent for classification.

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Give the agent access to all internal tools and let it infer the category from whichever tool it chooses to call.

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Build a multi-agent pipeline where a classifier agent debates a router agent until they agree on a category.

Question 2

An agent uses a retrieval tool that returns the top 20 chunks for any query. In production, the agent frequently cites irrelevant chunks and sometimes misses the correct answer even when it is present in the corpus. The corpus contains documents with overlapping terminology. Which architectural change most improves answer grounding without increasing the number of retrieved chunks?

Accepted Answer

Add a re-ranking stage that scores the retrieved chunks against the query and passes only the highest-scoring subset to the model.. The retrieval step is high-recall but low-precision, which is why irrelevant chunks are cited and correct ones are missed amid overlapping terminology. Adding a re-ranking stage that scores candidates against the query and passes only the top subset improves precision without retrieving more chunks, directly improving grounding and citation quality.

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Embed the entire corpus into the system prompt so the model always has full context available.

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Increase the retrieval count to 50 so the correct chunk is more likely to be included somewhere in the context.

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Lower the model's temperature to zero so it sticks more closely to the retrieved text.

Question 3

An orchestration agent runs a nightly workflow that fans out to 12 subagents, each calling a partner REST API. Partner calls intermittently return HTTP 429 with a Retry-After header. The orchestrator currently retries immediately in a tight loop, causing cascading 429s and duplicate side effects on the partner systems. Which architectural change best addresses both the throttling and the duplicate side effects?

Accepted Answer

Introduce a shared token-bucket rate limiter in front of the partner calls plus idempotency keys on every mutating request, with subagents respecting Retry-After.. Bursty fan-out against a rate-limited partner needs two coordinated controls: a shared limiter so the aggregate request rate stays under the partner's ceiling, and idempotency keys so a retried mutating call cannot create a second side effect. Honoring Retry-After aligns retry timing with the partner's guidance. Token or context changes operate on model text, not on outbound traffic, and serializing the workload removes parallelism without addressing throttling or duplication.

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Reduce the fan-out to a single subagent that processes all 12 partners sequentially with no retry logic at all.

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Switch every subagent to a larger context window so each can hold the full history of prior 429 responses and learn to avoid them.

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Increase the orchestrator's max_tokens so the model can reason longer about each 429 before deciding to retry.

Question 4

You are architecting a Claude-based agent for a regulated financial client that performs long-running portfolio rebalancing workflows. A compliance requirement mandates that no single trade instruction may be executed unless it is cryptographically traceable to the exact model-generated intent that produced it. The agent uses the Messages API with tool use, and several downstream services consume tool calls asynchronously. Which architectural mechanism best satisfies this requirement while preserving agent autonomy?

Accepted Answer

Persist every assistant turn containing a tool_use block, its tool_use id, and the matching tool_result, forming an immutable audit chain keyed by the tool_use id.. Binding each tool call to the platform-generated tool_use id and persisting the surrounding assistant turn creates a deterministic chain from model intent to executed instruction. Because the id appears in both the tool_use block and the tool_result, downstream services and auditors can reconcile them without trusting model-authored text. Caching, summaries, or self-hashes do not establish that binding.

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Require the model to emit a SHA-256 hash of its own reasoning text inside the tool input, and verify that hash in the downstream trade service before execution.

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Route all trades through a single orchestrator agent that logs a natural-language summary of each decision to an append-only ledger after the trade is confirmed.

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Enable prompt caching on the system prompt so that every trade instruction inherits a stable cache key that can be presented to auditors as proof of origin.

Question 5

Your team operates a Claude agent that triages inbound customer support tickets. After several weeks in production, the agent begins approving refunds above the policy ceiling and citing outdated policy text. Investigation shows the system prompt embeds a policy document that was updated three weeks ago, but the deployed prompt was never regenerated. Which architectural practice most directly prevents this class of failure?

Accepted Answer

Move policy content out of the system prompt and retrieve the current policy at runtime via a versioned tool or retrieval step, recording the version used in each decision.. Stale behavior traced to a frozen prompt is best solved by externalizing the mutable knowledge and fetching it at decision time from a versioned source. That way policy updates propagate immediately, and logging the retrieved version makes each action auditable. Compression, randomness, or peer review all leave the embedded copy as the de facto source of truth.

Answer

Add a second Claude agent that reviews the first agent's refund decisions and overrides any that appear inconsistent with its own recollection of company policy.

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Increase the model's temperature slightly so the agent explores alternative interpretations of the policy text it has memorized.

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Shorten the system prompt by summarizing the policy into a compact bullet list, which reduces the chance that outdated sections remain embedded.

Question 6

A retail company is building a governance program for a customer-facing Claude agent that can issue refunds and update order records. The risk committee wants controls that limit the blast radius of a compromised or misbehaving agent. (Choose two.)

Accepted Answer

Require human approval for refunds above a defined monetary threshold before the action is executed.. Blast-radius reduction requires preventive controls that bound what the agent can execute. Least-privilege tool scopes with per-action authorization shrink the callable action set, and threshold-based human approval stops high-value refunds before they happen. Logging, policy publication, and periodic transcript review are detective or administrative measures that document or discourage misuse but do not constrain the agent's real-time capabilities, so they fail the risk committee's objective.

Answer

Enable verbose debug logging of every prompt and response for later forensic review.

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Schedule quarterly reviews of the agent's conversation transcripts to identify emerging misuse patterns.

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Publish an acceptable use policy that prohibits employees from manipulating the agent.

Question 7

A fintech company's risk committee is operationalizing a governance program for Claude-powered customer support agents. They must demonstrate to regulators that model behavior changes are tracked, attributable, and reversible. Which TWO practices best satisfy this requirement? (Choose two.)

Accepted Answer

Run a fixed regression suite against each candidate model version and archive the scored results before promoting it.. Attributable, reversible model change management requires two things working together: a frozen, dated artifact in production and comparable evidence captured before promotion. Pinning to dated model identifiers supplies the frozen artifact and the rollback target, while a fixed regression suite run against each candidate supplies the before-and-after evidence. Together they let the risk committee answer what changed, who approved it, and how to undo it.

Answer

Route every request through a gateway that logs the full request and response payloads with the model identifier attached.

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Enable prompt caching on all production requests so that previously validated prompts are reused verbatim.

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Store the system prompt in a version-controlled repository and require pull-request review before it is merged.

Question 8

A multinational bank deploys Claude to draft internal policy summaries for staff in the EU and Singapore. Legal requires that personal data embedded in employee questions never leave its region of origin, but the bank wants a single application codebase. Which architecture most directly enforces the residency requirement?

Accepted Answer

Configure regional API endpoints so that EU traffic is served within the EU and Singapore traffic within its region, sharing only stateless application code.. Data residency is a geographic constraint on where processing happens, so the control must shape the request path rather than the contract or the retention window. Routing each jurisdiction to an in-region API endpoint keeps personal data inside its required boundary while a shared, stateless codebase avoids duplicated engineering effort. Redaction and retention settings reduce risk but do not guarantee the data never leaves the region.

Answer

Enable zero data retention on the account so that no request or response content is stored by the provider.

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Deploy the application in one region and rely on the model provider's contractual data processing addendum to cover cross-border transfer.

Answer

Apply client-side redaction of names and identifiers before the request is sent, then send all traffic to a single global endpoint.

Question 9

A hospital network is drafting its AI risk register for a Claude-based discharge-summary assistant. The governance lead wants entries that describe residual risk after existing controls are applied, and that can be assigned an owner and a review cadence. Which TWO characteristics must each risk register entry have to meet this standard? (Choose two.)

Accepted Answer

A residual risk rating that reflects the effect of the controls already in place.. An operational risk register entry must state the exposure that remains after controls and must have someone accountable for watching it on a schedule. Residual rating captures what is actually at stake post-mitigation, while owner and review interval ensure the entry is revisited and acted upon as the assistant and its clinical context change.

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A verbatim copy of the vendor's model card and system prompt.

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A list of every employee who has ever accessed the assistant.

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A projected cost saving attributed to deploying the assistant.

Question 10

A stakeholder asks for a change in the model's tone to be 'more professional' for customer support. How should you translate this request into technical requirements?

Accepted Answer

Create a clear system prompt with guidelines for tone, style, and vocabulary.. Translating subjective feedback like 'professional tone' into concrete system instructions is a core task for an architect. By creating a specific system prompt and testing it against a set of representative inputs, you define what 'professional' means for the system. This provides a clear, verifiable standard that ensures consistent communication across all customer support interactions, improving both the quality of service and the reliability of the AI implementation.

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Tell the stakeholder that tone is subjective and suggest we keep the default setting.

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Change the model version to one that is specifically advertised as 'professional'.

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Ask the stakeholder to rewrite the model's responses themselves to ensure it is correct.

Question 11

A regional sales director wants the Claude assistant to answer questions about competitor pricing using 'whatever is on the internet.' You know the assistant currently uses only approved internal documents. How should you frame the trade-off for the steering committee?

Accepted Answer

Present a comparison of retrieval sources covering accuracy, freshness, legal exposure, and cost, and recommend a scoped pilot with an approved external source.. When a stakeholder asks to broaden a data source, the architect's value is in structuring the trade-off rather than issuing a verdict. A source comparison across accuracy, freshness, legal exposure, and cost gives the steering committee the information to decide, and a scoped pilot with an approved external source limits risk while testing the premise. Blanket rejection, instant approval, and deflection all skip the analysis that makes the decision defensible.

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Reject the request because unapproved internet content can never be used in a Claude-based system.

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Approve it immediately and connect the assistant to a general web search tool without further analysis.

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Tell the director that competitor pricing is out of scope and should be handled by a separate team.

Question 12

A retail client's marketing director tells you the Claude-based product description generator is 'too slow' and wants it fixed by the end of the week. Before committing engineering effort, what should you do first?

Accepted Answer

Ask the director to define the target latency, the workflow step where it feels slow, and how many descriptions are generated per session, then measure current performance against that definition.. A vague performance complaint must be converted into measurable criteria before any engineering commitment. Asking for the target latency, the specific workflow step, and the typical session volume establishes both a baseline and an agreed success threshold. That measurement reveals whether the bottleneck is model generation, prompt size, batching, network overhead, or the surrounding application, so effort goes to the real constraint rather than a guess.

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Escalate to the account executive to reset expectations, explaining that large language model latency is inherent and cannot be improved.

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Agree to the deadline and immediately begin optimizing prompt length and switching to a smaller model to reduce latency.

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Convert the pipeline to streaming responses so text begins appearing in the UI sooner, which will resolve the perceived slowness.

Question 13

A business unit wants to reuse your Claude-based document summarization service for a new internal use case. They ask what they must provide before you can onboard them. Which response best reflects a sustainable internal platform operating model?

Accepted Answer

They must complete a standard intake form covering use case, data classification, expected volume, latency needs, and success metrics.. A sustainable internal platform model requires a consistent intake path so demand can be assessed, prioritized, and configured safely. A standard intake form captures use case, data classification, volume, latency, and success metrics, giving the platform team the information to evaluate fit and risk. This creates comparability across business units and prevents ad hoc onboarding that leads to rework, inconsistent safeguards, and unclear ownership of outcomes.

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They only need to send sample documents, and your team will infer the rest of the requirements.

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They must fund a dedicated instance of the service with its own separate codebase and deployment pipeline.

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They should open a support ticket whenever they are ready and the platform team will schedule a kickoff call.

Question 14

You are preparing a go-live readiness review for a Claude-powered advisory assistant used by field staff. The steering committee wants assurance that operational ownership is clear before launch. Which two artifacts are most essential to demonstrate that the lifecycle handover from project to operations is complete? (Choose two.)

Accepted Answer

A documented service ownership agreement naming the accountable team, support hours, and service level objectives.. A complete handover requires both a named owner and the operational procedures that owner will follow. The service ownership agreement establishes accountability, support hours, and service level objectives, while the signed runbook documents incident response, escalation, and maintenance. Together they give the steering committee confidence that the assistant will be sustained after the project team transitions away, rather than drifting without ownership or support coverage.

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A list of all stakeholders who attended the project kickoff meeting.

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A complete archive of every prompt version ever tested during development.

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A slide deck summarizing the assistant's key features for the marketing team.

Question 15

Why is it recommended to use structured output (like JSON) when building LLM-based applications?

Accepted Answer

It ensures the model response is easily consumable by downstream code.. Structured output ensures that the model's response is easily parsable by downstream systems, eliminating the need for complex, error-prone regex or natural language parsing. This enables seamless integration between AI components and existing backend services, which is vital for building reliable, production-grade software. It directly improves developer productivity by reducing the amount of 'glue code' needed to handle unpredictable text formats, leading to more stable and maintainable application architectures.

Answer

It makes the model run faster than returning unstructured text.

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It allows the model to compress the output into fewer tokens.

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It prevents the model from generating hallucinations.

Question 16

An architect wants to improve the coherence of an agent that frequently makes 'leaps of logic' or misses obvious errors in its tool outputs. Which TWO techniques directly address this behavior?

Accepted Answer

Chain-of-Thought (CoT) in the assistant turns. Coherence in agents is improved by forcing the model to externalize its reasoning and critique its own work. Chain-of-thought encourages the model to plan before acting, while self-reflection allows it to catch and correct its own mistakes in a subsequent turn, leading to much more reliable agentic behavior.

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Increasing the frequency of tool calls

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Reducing the temperature to exactly 0.0

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Using the 'tool_choice' parameter to force tool use

Question 17

When planning for the long-term support of an Anthropic API deployment, what is the most important stakeholder alignment activity?

Accepted Answer

Establish a roadmap for periodic model updates and performance validation.. Regular alignment on the evolving capabilities of the model and the corresponding updates to the application is critical. LLM technology evolves rapidly, and maintaining an alignment between new capabilities and the business roadmap ensures that the organization extracts maximum value over time. This keeps stakeholders engaged and ensures that the system doesn't become stagnant, providing a path for continuous improvement and innovation throughout the lifecycle of the AI integration.

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Ensure that the IT budget is fixed for the next five years to prevent cost fluctuations.

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Sign a lifetime contract with the current development team to avoid knowledge loss.

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Focus on manual documentation of every prompt to keep the system unchanged forever.

Question 18

Your team wants to adopt a 'Configuration-as-Code' approach for LLM prompts. Which tool is most suited for managing this?

Accepted Answer

A Git-based repository integrated with a CI/CD pipeline.. Version control systems (like Git) combined with modern CI/CD pipelines are the best tools for Configuration-as-Code. By treating prompts as code, teams gain the benefits of peer reviews, version history, and automated testing, which are essential for LLM operational enablement. This approach ensures that changes to model behavior are transparent, reproducible, and easily reversible, significantly reducing the risk of production incidents and improving team collaboration on prompt engineering tasks.

Answer

A shared Excel spreadsheet on a local company server.

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Directly updating the prompts in the model provider's web console.

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Hardcoding the prompts in a static configuration file inside the app binary.

Question 19

What is the primary role of a 'Model Card' in the context of enterprise AI governance?

Accepted Answer

A comprehensive summary of the model's performance, limitations, and intended usage.. Model Cards are essential documentation that provides transparency into a model's intended use, limitations, performance benchmarks, and known biases. For an enterprise architect, they serve as the technical source of truth for assessing whether a model is fit for a specific business use case. This documentation is critical for risk management, ensuring that deployments are grounded in a clear understanding of the model's capabilities and boundaries.

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A list of all API keys associated with the model for billing purposes.

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A tool for automatically deploying the model to production environments.

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A physical card used for multi-factor authentication to access the API.

Question 20

When implementing AI safety policies, which THREE components should be included to ensure effective operationalization?

Accepted Answer

Clearly defined prohibited use cases.. Operationalizing safety policy requires a combination of clear guidelines, technical enforcement, and feedback mechanisms. Without all three, policies remain abstract documents that are difficult to follow. Effective governance requires that these policies are baked into the CI/CD pipeline, audited regularly, and enforced by technical tools like guardrails, ensuring that the organization can maintain a consistent safety posture across all AI applications and development teams.

Answer

The ability to ignore rules during testing.

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Complete removal of human oversight.