Pass Guaranteed 2026 Latest Anthropic CCAR-P: Answers Claude Certified Architect - Professional Real Questions

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Anthropic CCAR-P Exam Syllabus Topics:

SectionObjectives
Enterprise Integration and Production- Enterprise integration architecture and production readiness
- Cost, latency, reliability, and operational design
Stakeholder Engagement and Solution Lifecycle- Stakeholder discovery and architectural trade-off communication
- Solution lifecycle, handoff, adoption, and operational enablement
Evaluation and Optimization- Evaluation design and acceptance criteria
- Model and architecture optimization
Solution Design- Claude platform and solution architecture
- Model, architecture, context, and deployment strategy selection
Governance, Safety, and Risk- Security, compliance, risk management, and governance
- Safety controls and fail-closed system design

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Anthropic Claude Certified Architect - Professional Sample Questions (Q104-Q109):

NEW QUESTION # 104
You are distinguishing functional from non-functional requirements during discovery.
Which item is a non-functional requirement?

Answer: A

Explanation:
Option D defines a measurable performance characteristic rather than a business capability. The requirement specifies a percentile-based latency threshold-under 800 milliseconds at the 95th percentile-and ties that threshold to the expected workload volume. It therefore describes how well the system must operate under defined conditions.
Options A, B, and C are functional requirements. They describe actions the solution must perform: extracting fields and creating a downstream record, producing an editable draft, and assigning tickets to categories.
Functional requirements define observable system behaviors or outputs.
A strong non-functional requirement must include a metric, threshold, measurement method, and operating condition. For Option D, the architect should further define whether latency is measured end-to-end or only at the model API, the test duration, concurrency, input-size distribution, cache state, timeout behavior, geographic region, and treatment of failed requests. Without those details, teams may report incompatible results while claiming to satisfy the same requirement.
Non-functional requirements for Claude solutions commonly address latency, availability, throughput, cost, privacy, security, recoverability, observability, scalability, and regulatory compliance.
Study Guide references/topics: Structured discovery; functional requirements; non-functional requirements; p95 latency; workload conditions; measurable acceptance criteria.


NEW QUESTION # 105
You are selecting the documentation set that should accompany a Claude-based deployment at handoff.
Which set is most complete?

Answer: B


NEW QUESTION # 106
You are selecting a model for a new production workload and must complete the upstream steps before testing candidate models empirically.
Which two steps must be completed BEFORE running a representative sample on a candidate model? (Select two.) Each correct answer presents part of the solution.

Answer: C,D


NEW QUESTION # 107
You are reviewing a peer's end-to-end design for a Claude-based platform expected to scale to thousands of concurrent users.
For each statement, indicate Yes if it reflects sound architectural practice. Otherwise, select No.

Answer:

Explanation:

Explanation:
* Authentication and authorization run before retrieval so retrieval can filter by identity - Yes
* An asynchronous queue absorbs bursty traffic between intake and the model-invocation layer - Yes
* Tax computation is encoded directly in the system prompt rather than in code - No
* Conversation logs include unredacted government identifiers to maximize tuning signal - No Authentication and authorization must precede retrieval so unauthorized information never enters model context. An asynchronous queue is appropriate for burst absorption, backpressure, controlled concurrency, and retry management at scale. Deterministic tax computation should be implemented in validated code or a controlled calculation tool, not delegated to probabilistic prompt interpretation. Including unredacted government identifiers in conversation logs violates data-minimization principles and creates unnecessary privacy, security, and regulatory exposure. Sensitive fields should be removed, tokenized, or redacted before logging or model use unless specifically required and authorized. The resulting design separates deterministic computation, access control, scalable orchestration, and language reasoning into appropriate architectural layers.


NEW QUESTION # 108
You are operating an interactive assistant whose dominant performance constraint is per-turn latency. Quality on routine turns is already acceptable.
Which configuration adjustment most directly improves latency without disproportionately damaging quality?

Answer: D

Explanation:
Option B targets two major contributors to per-turn latency: retrieved-context size and repeated prompt processing. Reducing retrieval to an empirically validated top- k limits the tokens Claude must process while preserving the passages that historically provide sufficient answer coverage. Caching the stable system- prompt prefix avoids repeatedly processing identical instructions.
Anthropic's latency guidance recommends choosing an appropriate model and reducing unnecessary input and output tokens. Its prompt-caching documentation explains that caching reusable prompt prefixes can reduce both repeated processing cost and latency. Reducing Latency , Prompt Caching The retrieval depth must be selected through evaluation rather than arbitrary truncation. The team should compare answer quality, retrieval recall, latency, and failure rates across candidate values and retain escalation logic for complex queries requiring deeper retrieval.
Option A removes an applicable latency optimization. Option C maximizes context consumption regardless of demonstrated benefit. Option D deliberately selects the slowest model class even though routine-turn quality already meets requirements.
Study Guide references/topics: Latency optimization; top- k retrieval; prompt caching; token reduction; quality-latency evaluation; adaptive retrieval.


NEW QUESTION # 109
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