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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

A Claude application that worked well in testing is now occasionally returning outputs that mention information not present in the input. The development team initially assumed the model was hallucinating, so they asked you to troubleshoot.
What would you do first?

A. Replace the current model with a larger one to reduce the chance of hallucination, on the grounds that larger models tend to hallucinate less in typical applications.
B. Examine production traces to identify whether the issue is hallucination by the model, context loss, prompt injection, or another failure mode before recommending a fix.
C. Add a system prompt instruction telling the model not to invent information, on the grounds that prompt-level instructions are the fastest fix for hallucination concerns.
D. Apply a retrieval-augmented generation pattern to ground the responses in source content before any further investigation of the production traces.

Question 2

You are running Claude Code as part of an automated continuous integration pipeline. The pipeline needs Claude Code to execute a set of well-defined tasks without prompting for confirmation, and the output needs to be captured for downstream processing.
How would you configure the pipeline?

A. Disable Claude Code's confirmation prompts globally across all environments so the pipeline runs without interruption from any prompt.
B. Replace Claude Code with a different tool that does not require any configuration to operate without confirmation prompts in the pipeline.
C. Run Claude Code in headless mode with the required permissions configured in settings.json and capture its output for downstream processing.
D. Run Claude Code in interactive mode and have a developer manually approve every confirmation prompt while the pipeline executes its tasks.

Question 3

The Anthropic API deprecated a request parameter that your Claude application uses in approximately 40 places across the codebase. The deprecation notice gives a six-month window before the parameter is removed and recommends a replacement parameter with slightly different semantics.
You would respond to the deprecation by...

A. Adding regression tests to cover the parameter's behavior, then migrating call sites in batches that you validate against regression tests.
B. Swapping all 40 call sites in a single change right away to prevent drawn-out migration work that will delay ongoing functioning.
C. Keeping the deprecated parameter in place while writing a wrapper function around it to insulate the rest of the codebase from the eventual change.
D. Migrating all 40 call sites in a single change near the removal date to ensure the deprecated parameter continues to work as long as possible.

Question 4

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.

Question 5

Your Claude application is hitting context window limits when processing long customer service transcripts.
A junior developer suggests increasing the temperature parameter to fix the issue.
How would you respond?

A. Adjust the temperature parameter together with the max_tokens parameter, treating the combined adjustment as the team's mechanism for managing context window pressure during long-transcript processing.
B. Explain that temperature controls sampling randomness and is unrelated to context capacity, then address the context issue through summarization or chunking.
C. Increase the temperature parameter as the junior developer suggested and observe whether the context window issue resolves over the next several runs of the application in production.
D. Remove the system prompt entirely to make room for longer transcripts in each request, freeing up context window space the system prompt would otherwise consume.

Solutions: