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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

The team is debating whether to build a new capability as a custom tool or to use an existing built-in tool that nearly covers the use case but lacks one specific feature.
How would you decide?

A. Examine the custom tool option by scoping the implementation effort and determining whether the additional flexibility justifies the development and maintenance cost.
B. Identify whether the team has previously built similar custom tools and use those precedents to determine which approach is more consistent with the existing codebase.
C. Evaluate whether the missing feature can be addressed by extending the built-in tool or warrants a custom tool, then choose accordingly.
D. Review the built-in tool's documentation and assess whether its existing capabilities are sufficient to cover the use case without any modification or extension.

Question 2

You maintain a Claude application that uses Claude Sonnet 4.5 across several production workflows.
Anthropic released Claude Sonnet 4.7, which your evaluation suite shows performing 8% better on your highest-volume task. However, this version produces different output formatting on two of your structured- extraction prompts that downstream consumers parse with regex-based code.
To roll out the upgrade, you would...

A. Switch the model identifier in the application's configuration to the new model, then monitor production for parsing failures to be fixed as failures surface.
B. Keep the older model in production to preserve the fragile parsing layer that may risk breaking with any model change.
C. Adjust the prompts to constrain output format, re-run evaluations against the expected parsing-layer schema, then roll the model out with a feature flag and the option to revert per workflow.
D. Rewrite the downstream parsing code to accept a wider range of output formats to ensure the application is resilient to future model upgrades without requiring prompt changes.

Question 3

You are explaining to a stakeholder why running the same Claude prompt twice can produce slightly different results. The stakeholder is concerned this means the application is broken.
How would you address the stakeholder's concern?

A. Explain that LLMs are non-deterministic by default due to sampling, and describe how the application handles this through validation, retries, or temperature adjustment.
B. Tell the stakeholder the variation is a bug that the team will fix in the next release of the application, then create a work ticket to fix the bug.
C. Tell the stakeholder the variation is caused by Claude being updated continuously by Anthropic, and that switching to a fixed model snapshot will eliminate the variation entirely.
D. Tell the stakeholder the variation comes from network latency and that switching to a faster network connection will produce more consistent results across runs.

Question 4

Your Claude application is deployed to development, staging, and production environments. Each environment uses a different model version, different prompt versions, and different plugin dependencies, but the configuration is currently scattered across environment variables, hardcoded values, and undocumented setup scripts.
How would you manage the configuration?

A. Use the latest available model version everywhere and stop pinning model versions, on the grounds that pinning adds maintenance overhead the team should aim to reduce.
B. Move all configuration into hardcoded application code to reduce reliance on external configuration sources that are difficult to track over time.
C. Standardize all environments to use the same configuration values to eliminate the differences between development, staging, and production.
D. Consolidate the configuration into a version-controlled system documenting model version pinning, prompt versioning, and plugin dependencies for each environment.

Question 5

Your Claude application receives untrusted input from external sources. The team is establishing how the application should treat this untrusted input.
Untrusted input would be...

A. Validated and sanitized before being incorporated into prompts, and treated as data the model should not interpret as instructions.
B. Treated identically to trusted input from internal sources, on the grounds that all input the application receives can be handled the same way.
C. Blocked entirely so the application accepts only trusted input, with no path for legitimate external input the application might process.
D. Routed through a separate Claude application with more lax security controls so the original application does not handle the untrusted input directly.

Solutions: