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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

Your Claude application's token costs have grown faster than expected. The team has not been tracking token usage by feature, so the team cannot identify which features are driving cost. The team is debating how to respond.
How would you respond?

A. Add token usage tracking by feature to the application's logging so the team can identify which features drive cost before recommending changes.
B. Tell the team that cost growth is unavoidable as the application scales and that no investigation will change the trajectory of the application's cost over the next several quarters.
C. Switch every feature to the smallest model to cut cost broadly across the application during normal operation.
D. Reduce token usage uniformly across all features by half, applying the cut evenly across the application during normal operation.

Question 2

Your Claude application returns confident-sounding answers, but occasionally those answers contain factual errors that downstream systems treat as ground truth. The team is concerned about the application's confidence-versus-accuracy gap.
How would you address the gap?

A. Reject every response the application produces until a manual accuracy review is conducted on each response by a human reviewer before any downstream system uses it.
B. Apply skepticism toward confident output by adding validation steps, sourcing requirements, or confidence calibration before treating outputs as ground truth.
C. Add a disclaimer to every output telling users to verify the accuracy of the output and treat the disclaimer as the primary mechanism for managing the confidence-versus-accuracy gap.
D. Lower the model's temperature so the model's responses sound less confident and downstream systems are less likely to treat the responses as ground truth in normal operation.

Question 3

You are setting up a Claude application that will run a mix of multi-turn conversations and one-off requests.
You want to use caching techniques to reduce token costs where they apply. A teammate suggests caching the model's output as well, so the application does not have to make duplicate Claude calls when similar queries arrive.
You would apply prompt caching to...

A. Nothing, because prompt caching does not affect cost in any application that mixes multi-turn conversations and one-off requests in a single deployment.
B. Only the user's input portion of each request because user input is the part of the prompt that varies the most across the application's normal operation.
C. The model's output, treating the response from each request as cacheable content the application can return on similar future queries.
D. The static portions of prompts that are repeated across requests, such as system prompts, instructions, or shared context.

Question 4

A teammate has asked why your Claude application sometimes produces a response that includes the prompt text repeated back, and other times produces a response with the prompt text rephrased. They suspect a bug in the application's request construction.
How would you respond?

A. Tell the teammate that the variation depends on which Claude model serves the request, and recommend pinning the application to a single model version to make the output behavior consistent.
B. Tell the teammate that the variation is caused by the application sending two different prompts on different runs and propose a code change that pins the system prompt to a single version.
C. Explain that LLMs generate output token by token, and variation in how prompt content appears in output is a property of generation, not a bug in request construction.
D. Confirm that the variation is a bug in the application's request construction and start investigating which part of the application is producing the inconsistent prompt text.

Question 5

You are writing a system prompt for a Claude application that needs to produce output in a specific JSON shape. The downstream system will reject any output that does not match the schema.
Your prompt would need to...

A. Omit any reference to the format and rely on a post-processing step in the application to reshape Claude's output.
B. Include explicit constraints describing the required JSON schema and an instruction to produce only output matching that schema.
C. Instruct Claude to return JSON sometimes and free text other times so the application's output captures both formats.
D. Instruct Claude to use whichever output format it considers most appropriate for each request the application handles.

Solutions: