Claude Certified Architect Professional CCAR-P Exam Questions

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Question #16 (Topic: Demo Questions)

A client insists on an agentic architecture because a competitor announced one, although discovery shows their process is a fixed, well-understood five-step sequence. How should the architect respond?

Present the comparison on the client's own terms — what each option costs, how each performs, how each is tested and debugged — and recommend the workflow, while designing clear extension points should genuinely variable cases emerge.

Build the agentic system as requested, since the client is paying and has stated a preference.

Build the workflow but describe it as agentic in project documentation.

Refuse the engagement on the grounds that the requested architecture is inappropriate.

Correct Answer: A

Explanation:

Why this is correct. The architect's obligation is to inform the decision, not to win the argument or defer to it.

Presenting cost, performance, testability, and debuggability in the client's own terms gives them a basis to choose, and clients who arrived at a preference through market signals usually update readily once the tradeoffs are concrete. The extension-points clause is what makes this collaborative rather than dismissive: it acknowledges the client's underlying concern — that the process may not stay fixed — and designs for it, so the recommendation is not simply "you are wrong."

Why B is wrong. Building a known-inappropriate architecture without objection abdicates the advisory role the client is paying for. When it costs more and proves harder to debug, the client will reasonably ask why nobody said so.

Why D is wrong. Refusal is a disproportionate response to a disagreement that has not yet been discussed. It is also a failure of the influencing skill the role requires — architects routinely change minds by presenting

evidence, and this scenario has not reached an ethical boundary.

Why C is wrong. Misrepresenting what was built is a straightforward integrity failure. It also creates a concrete future problem: the documentation will mislead whoever maintains the system, and the deception surfaces the moment anyone technical reads the code.

Blueprint objective: Communicate architectural decisions and trade-offs; manage stakeholder expectation alignment.

Question #17 (Topic: Demo Questions)

A client opens a discovery session by saying, "We want to use AI to improve customer service." What is the most effective next step for the architect?

Run structured discovery to establish the current process, its measurable pain points, what success would look like numerically, what constraints exist, and who owns the outcome.

Propose a reference architecture for a customer service assistant based on similar past engagements.

Request access to the client's ticketing system so the data can be analyzed immediately.

Ask which Claude model the client would prefer to use.

Correct Answer: A

Explanation:

Why this is correct. "Improve customer service" is an aspiration, not a requirement. Structured discovery converts it into something buildable by establishing the current process and its actual failure points, a quantified definition of success (deflection rate, first-response time, CSAT — with a target), the constraints that bound the solution space (regulatory, data residency, systems that cannot be changed, budget), and crucially who owns the outcome and will make decisions. Skipping this is the most common cause of projects that deliver working software nobody adopts, because the team solved the problem they assumed rather than the one that

exists.

Why B is wrong. Proposing an architecture before understanding the problem imports assumptions from a different client's context. It also anchors the conversation on a solution, which makes it socially awkward for the client to reveal facts that would invalidate it.

Why D is wrong. Model selection is a late, evaluation-driven decision that depends on task requirements, latency budgets, and cost constraints — none of which are known yet. Asking a client to choose it is asking the wrong person the wrong question at the wrong time.

Why C is wrong. Data analysis is valuable but premature, and requesting production data access in the opening minutes raises governance questions before any purpose has been established. Understand the problem first; the data will be more informative once you know what you are looking for.

Blueprint objective: Conduct structured discovery and requirement gathering.

Question #18 (Topic: Demo Questions)

An executive sponsor asks why the proposed system uses retrieval rather than "just having the AI learn our documents." Which explanation is most effective for this audience?

Explain that training a model on the documents is technically impossible.

State that retrieval is the industry-standard approach for enterprise deployments.

Explain that retrieval lets the assistant look up the current document at the moment of the question — so updates take effect immediately, answers can cite their source, and there is no retraining cost or delay when policies change.

Explain the mathematics of embedding spaces and vector similarity search.

Correct Answer: C

Explanation:

Why this is correct. Effective communication with a non-technical sponsor translates architecture into consequences the sponsor cares about, using an accurate mental model rather than a simplified-to-the-pointof-wrong one. "Looks it up when asked" is both true and immediately intuitive, and it yields three businessrelevant implications: changes take effect at once, answers are attributable to a source the business can verify, and there is no retraining cycle or cost each time policy changes. The sponsor can now evaluate the decision rather than merely defer to it.

Why A is wrong. Embedding mathematics answers a question the sponsor did not ask. Correct but unusable information erodes confidence — the sponsor concludes the architect cannot explain the decision, which is often what they were really testing.

Why C is wrong. An appeal to industry standard is an argument from authority that gives the sponsor no basis

for judgment. It also fails immediately if someone in the room asks "but why is it standard?"

Why D is wrong. It is false — models can be trained on documents. Winning an objection with an inaccurate claim is a serious credibility risk, since it takes one informed person in the room to unravel it.

Blueprint objective: Communicate architectural decisions and trade-offs.

Question #19 (Topic: Demo Questions)

Evaluation shows a proposed document classification system will be correct about 93% of the time. The business sponsor expects "AI accuracy," which they describe as near-perfect. What is the most appropriate way to handle this expectation gap?

Commit to 99% accuracy and treat closing the gap as an engineering problem to be solved later.

Present the 93% figure early alongside the current human baseline, the cost profile of each error type, and the design's containment measures — then agree an accuracy target and a review path as part of the SLA.

Report the system's accuracy on its best-performing category to build confidence.

Delay the conversation until the system is in production and the sponsor observes the error rate directly.

Correct Answer: B

Explanation:

Why this is correct. The gap is between an expectation and a measured reality, and it is best closed with context rather than either concealment or capitulation. The human baseline is the essential comparison — if the existing manual process is 89% accurate, 93% is an improvement rather than a shortfall, and sponsors routinely hold automated systems to a standard they never applied to people. Error cost profiling reframes the discussion productively, since a 7% error rate concentrated in cheap, easily corrected cases is very different from 7% concentrated in expensive ones. Ending with an agreed target and review path in the SLA converts a

vague expectation into a shared, measurable commitment.

Why A is wrong. Deferring a known gap until production guarantees the conversation happens at the worst possible moment — after launch, in front of an unhappy sponsor, with trust already damaged. Expectation misalignment is cheapest to fix early.

Why B is wrong. Presenting the best-performing slice as though it were overall performance is misleading by selection. When the real number surfaces, and it will, the architect's credibility on every other claim goes with it.

Why D is wrong. Committing to a number you have no evidence you can reach creates a contractual obligation on a hope. This is how projects acquire an unachievable success criterion that follows them to the end.

Blueprint objective: Manage stakeholder feedback loops and expectation alignment (including SLAs)

Question #20 (Topic: Demo Questions)

An architect is preparing handoff documentation for the client's internal team, who will own the system after go-live. Select TWO items that are most essential to include.

The personal contact details of each consultant who worked on the project.

The evaluation suite and its baseline results, with instructions for running it and interpreting a regression.

The rationale behind key architectural decisions, including options considered and why they were rejected.

A transcript of every design meeting held during the engagement.
E. A list of every Claude model available at the time of writing.

Correct Answer: B, C

Explanation:

Why this is correct. These are the two artifacts that determine whether the receiving team can safely change the system. The evaluation suite with baselines (B) is the safety net: without a way to run tests and recognize a regression, the new owners must either freeze the system or change it blind, and both are failure modes.

Decision rationale including rejected options (C) prevents the most predictable post-handoff mistake — a new owner "fixing" something that was a deliberate trade-off, then rediscovering the original problem the hard way.

Recording why an option was rejected is what makes the document durable, because it answers the question the next engineer will actually have.

Why D is wrong. Raw meeting transcripts are unfiltered volume. The signal they contain — the decisions and their reasoning — is exactly what C captures in usable form; the rest is noise that makes the documentation less likely to be read.

Why E is wrong. A model catalogue is public, freely available, and stale within months. Documentation should record what your system does and why, not restate the vendor's product list.

Why A is wrong. Individual contact details are not a support model. Handoff should define a supported escalation path and ownership, which survives people changing jobs.

Blueprint objective: Document architectures and provide implementation guidance; support lifecycle phases.

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