📘 Free CCAR-P Sample Questions
A logistics company wants Claude to process inbound freight quotes. Every request follows the same steps: extract shipment details from an email, validate them against a rate card, and generate a quote document. Requirements are stable and the steps never vary. Which architectural pattern is most appropriate?
A
A multi-agent system with a supervisor agent delegating to specialist agents
B
A fixed workflow where each step is a discrete, sequenced LLM call
C
An autonomous agent with tool access that plans its own approach per request
D
A single monolithic prompt containing all instructions and the full rate card
Correct Answer:
B. A fixed workflow where each step is a discrete, sequenced LLM call
Explanation:
The task is stable, repeatable, and fully known in advance — the textbook case for a fixed workflow, which gives predictability, per-step auditability, and easy debugging.
Why not the others: A adds multi-agent coordination overhead the problem doesn’t need; C adds autonomous planning overhead the problem doesn’t need; D sacrifices step-level control and validation.
A consultancy is building a research assistant that must investigate open-ended client questions. The steps required vary enormously between requests: some need three web searches, others need document analysis, calculations, and follow-up queries whose necessity only becomes clear mid-task. Which pattern best fits?
A
A fixed workflow with a generous number of pre-defined steps to cover most cases
B
A router that classifies each request into one of five pre-built pipelines
C
A batch process that runs every possible analysis on every request and discards unused output
D
An autonomous agent that plans, acts, observes results, and decides its next step in a loop
Correct Answer:
D. An autonomous agent that plans, acts, observes results, and decides its next step in a loop
Explanation:
When the path to the answer only emerges during execution, an autonomous plan–act–observe loop is the pattern designed for it.
Why not the others: A assumes the steps can be enumerated in advance; B still requires the path to be known up front; C is wasteful and still can’t follow up on intermediate findings.
A single prompt asks Claude to read a 60-page RFP, assess compliance against 40 internal policies, score the opportunity, and draft a go/no-go recommendation. Output quality is inconsistent: some policies are skipped and the scoring rationale is shallow. The team has already refined the prompt wording twice.
What is the most effective next step?
A
Move to the largest available model and increase the maximum output tokens
B
Add more few-shot examples of well-written go/no-go recommendations to the existing prompt
C
Decompose the task into sequenced subtasks (extract, assess per policy group, score, then synthesise), passing structured output between steps
D
Lower the temperature so the model follows the instructions more deterministically
Correct Answer:
C. Decompose the task into sequenced subtasks (extract, assess per policy group, score, then synthesise), passing structured output between steps
Explanation:
The failure signature — skipped items and shallow reasoning on a long, multi-part task — is a decomposition problem. Sequenced subtasks let each step receive focused context and produce verifiable intermediate output.
Why not the others: A treats capacity as the issue when structure is; B adds examples where structure, not guidance, is the gap; D affects randomness, not coverage.
A claims-processing solution uses four specialist agents: intake, fraud screening, policy validation, and payout calculation. The business requires a complete, ordered audit trail of every decision, and later agents must not run if an earlier agent flags an exception. Which orchestration strategy best satisfies these requirements?
A
A supervisor/orchestrator that invokes each specialist in sequence, records outcomes, and halts the chain on an exception
B
Peer-to-peer handoffs where each agent decides which agent to invoke next
C
Running all four agents in parallel and merging their outputs at the end
D
A shared message board that all agents monitor and respond to opportunistically
Correct Answer:
A. A supervisor/orchestrator that invokes each specialist in sequence, records outcomes, and halts the chain on an exception
Explanation:
A supervisor gives central sequencing, a single point to record the ordered audit trail, and the ability to halt on exception — all three stated requirements.
Why not the others: B makes ordering and halting emergent rather than guaranteed; C violates the requirement that later stages not run after a flag; D leaves sequencing and exception handling to chance rather than guarantee.
An executive sponsor wants to “put AI across the whole business” and asks the architect to propose the first project. Twelve candidate use cases have been suggested by different departments. What should most strongly drive the selection of the initial use case?
A
Choosing the use case that showcases the most advanced agentic capabilities
B
Selecting the department with the most enthusiastic stakeholders to guarantee adoption
C
Measurable business value (e.g. cost, efficiency, or an SLA improvement) combined with feasible data access and manageable risk
D
Whichever use case can go live fastest, regardless of impact, to build momentum
Correct Answer:
C. Measurable business value (e.g. cost, efficiency, or an SLA improvement) combined with feasible data access and manageable risk
Explanation:
First projects should be selected on measurable value pillars balanced against feasibility and risk that’s what builds durable organisational support.
Why not the others: A optimises for spectacle; B optimises for politics; D optimises for speed over demonstrable value.
A document-triage solution has been in production for three months. The team has latency and cost dashboards but no way of knowing whether the model’s classifications are actually correct in production. Which architectural addition most directly closes this gap?
A
A larger model, since classification accuracy generally improves with model capability
B
An alert that fires whenever daily token consumption deviates from the norm
C
A weekly review of the system prompt to check the instructions are still current
D
A feedback loop: capture downstream corrections and user signals, and route a sample of production outputs into a labelled evaluation set
Correct Answer:
D. A feedback loop: capture downstream corrections and user signals, and route a sample of production outputs into a labelled evaluation set
Explanation:
The missing architectural element is the feedback stage of the input?processing?output?feedback loop: production correctness signals flowing back into an evaluable dataset.
Why not the others: A changes the model without measuring anything; B monitors cost, not correctness; C monitors configuration, not correctness.
A retailer’s product catalogue, pricing, and promotions change daily. The team wants Claude to answer customer questions using this information and is debating how to give the model access to it. Which approach is most appropriate?
A
Fine-tune a model on the current catalogue and repeat the process each quarter
B
Augment the model with retrieval over the live catalogue so answers reflect current data
C
Paste the full catalogue into every request’s context window
D
Rely on the base model’s knowledge and add a disclaimer that prices may vary
Correct Answer:
B. Augment the model with retrieval over the live catalogue so answers reflect current data
Explanation:
Daily-changing factual data is the canonical case for retrieval augmentation — the model always answers from current data without retraining.
Why not the others: A is stale within days; C is costly and won’t scale with catalogue size; D simply accepts wrong answers.
A single “operations agent” handles HR queries, IT tickets, and finance requests. It has 35 tools, a 6,000-token system prompt covering all three domains, and its tool-selection accuracy has been declining as capabilities were added. Stakeholders want to add procurement next. What is the strongest architectural recommendation?
A
Split the agent into domain-specific agents behind a router or supervisor, each with a focused toolset and prompt
B
Add the procurement tools now and plan a prompt rewrite in the next quarter
C
Keep one agent but double the system prompt length so every domain is covered in more detail
D
Force the model to use a tool on every request so it stops answering from general knowledge
Correct Answer:
A. Split the agent into domain-specific agents behind a router or supervisor, each with a focused toolset and prompt
Explanation:
Declining tool selection as breadth grows is the classic signal that one agent is overloaded. Domain-specific agents behind a router restore focused prompts and toolsets, and make procurement an addition rather than a further burden.
Why not the others: B compounds the problem; C makes the prompt harder to follow, not easier; D misdiagnoses the failure.
An architect is deciding between a fixed workflow and an autonomous agent for a new solution. Which TWO characteristics of the problem most strongly favour the fixed workflow?
A
Inputs arrive in unpredictable formats requiring dynamic handling
B
The processing steps are known in advance and are the same for every request
C
The task benefits from creative exploration of multiple solution paths
D
The business requires each step to be individually auditable and reproducible
E
The team wants the model to recover autonomously from unexpected tool failures
Correct Answer:
B. The processing steps are known in advance and are the same for every request
Explanation:
Fixed workflows shine when steps are known and identical per request, and when auditability and reproducibility of each step matter.
Why not the others: A is a condition favouring agentic autonomy; C rewards dynamic planning, not fixed sequencing; E calls for autonomous recovery — the opposite of a fixed sequence.
A team is assessing whether a complex due-diligence task justifies a multi-agent design instead of a single augmented agent. Which TWO characteristics of the task most strongly indicate that multiple agents are warranted?
A
The overall request volume is expected to be very high
B
The project budget is large enough to afford multiple agents
C
Distinct sub-tasks require different specialisations, tools, and context that would overload a single agent
D
Stakeholders have asked for the most sophisticated architecture available
E
Several sub-tasks are independent and can run in parallel to reduce end-to-end time
Correct Answer:
C. Distinct sub-tasks require different specialisations, tools, and context that would overload a single agent
Explanation:
Multi-agent designs earn their complexity when sub-tasks need genuinely different specialisations/tools/context, and when independent sub-tasks can run in parallel.
Why not the others: A is a scaling concern solvable within any pattern; B is a budget fact, not an architectural driver; D is prestige, not an architectural driver.
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