Exam CCAR-P Topic 1 Question 112 Discussion

Actual exam question for Anthropic's CCAR-P exam
Question #: 112
Topic #: 1

The platform team at Trenova Systems, Inc. needs to reduce per-query cost and p95 latency for a high-volume Claude pipeline without degrading output quality on the core use case.
Which two optimizations directly target both cost and latency simultaneously? (Select two.)

A. Enable prompt caching on the static system-prompt prefix to reduce billable input tokens on repeated calls. B. Route straightforward query types to a smaller, faster Claude model and reserve the full model for complex cases. C. Increase max_tokens to reduce the frequency of truncated responses requiring follow-up calls. D. Add a retrieval step that fetches the full source corpus into the context window before generation. E. Expand the system prompt to include additional few-shot examples on every request.

Suggested Answer: A,B Vote an answer

Prompt caching reduces repeated input processing when a stable system prefix is reused, directly lowering input cost and processing latency. Model routing provides the second optimization: routine cases can use a faster, lower-cost model, while difficult cases retain access to the more capable model. The routing policy must be validated against representative evaluations to confirm that quality remains within the required threshold. Increasing max_tokens can increase output cost and generation time. Retrieving the complete corpus and adding examples to every request both enlarge the input, worsening latency and token consumption. Anthropic identifies prompt caching as a cost-and-latency optimization and recommends selecting a model according to the workload's quality, speed, and economic requirements. Prompt caching ; reducing latency

by Alexia at Aug 24, 2026, 11:46 AM

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