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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

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. Keeping the deprecated parameter in place while writing a wrapper function around it to insulate the rest of the codebase from the eventual change.
C. Swapping all 40 call sites in a single change right away to prevent drawn-out migration work that will delay ongoing functioning.
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 2

You are configuring Claude Code for a new project. The team needs to set permissions, default model selections, and environment-specific behavior at the project level so the configuration is consistent across all developers working on the repository.
The Claude Code mechanism you would use is...

A. A shared spreadsheet that lists configuration values for team members to reference and update by hand as the project evolves.
B. Environment variables that each developer sets on their own machine when working with Claude Code on the project.
C. The settings.json file, scoped at the project level so the configuration applies consistently across developers and persists with the repository.
D. A system prompt embedded in every Claude Code conversation by each developer at the start of every session in the project.

Question 3

Your agent is processing tasks that take 30 to 60 minutes to complete. Each task has well-defined intermediate checkpoints, and the team wants the agent to be able to resume from the most recent checkpoint if a process is interrupted.
How would you implement this resumability?

A. Apply a checkpointing pattern that persists the agent's intermediate state and reloads that state when resuming an interrupted task.
B. Restart the task from the beginning whenever a process is interrupted.
C. Increase the agent's timeout to several hours so that interruptions become rare enough to ignore in practice.
D. Run two copies of the agent in parallel for every task and use whichever one finishes first as the source of truth.

Question 4

Your Claude application processes 50-page legal contracts and produces summaries with citation references back to the source. The team is debating whether to send each contract whole or split it into smaller pieces.
The contracts fit within Claude's context window. Initial testing shows that whole-document processing produces summaries with stronger cross-section reasoning but occasionally drifts on citation accuracy in later sections. Chunked processing produces stronger citation accuracy per chunk but loses cross-section reasoning.
The team has not decided which property matters more.
How would you guide the team's decision?

A. Identify which property matters more for the application's actual use case and let that decision drive the chunking approach, then validate the choice against representative contracts.
B. Examine the use cases where cross-section reasoning failures occur and assess whether whole- document processing meets the application's accuracy requirements across a representative sample of contracts.
C. Review the citation accuracy results from chunked processing and determine whether the loss of cross- section reasoning produces summaries that still meet the application's quality bar.
D. Assess the cost and latency implications of both approaches against the application's performance requirements before recommending which processing strategy to adopt.

Question 5

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

Solutions: