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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

Your Claude agent's hooks are currently triggered for every action, which slows down the agent significantly even when actions pose no risk. The team wants to scope hooks more carefully.
How would you scope the hooks?

A. Replace hooks with system prompt instructions on the grounds that prompt instructions can produce the same enforcement effect that hooks produce on the agent's actions.
B. Scope hooks to only the high-risk actions, such as destructive operations or sensitive data access, and remove hooks from low-risk actions to balance safety with performance.
C. Disable all hooks while the team re-scopes them, treating the period of no hook enforcement as a temporary state during the re-scoping work.
D. Disable the agent during peak hours so the hook overhead does not slow the application down during the busiest periods of the day across the application's operation.

Question 2

You are designing a Claude application that helps medical researchers analyze multi-step clinical case studies.
The application must work through differential diagnoses by considering symptom patterns, weighing evidence across competing hypotheses, and showing intermediate reasoning steps before producing a final recommendation. The team is choosing among Claude's available model options.
The model option best suited to this use case is...

A. A smaller model with a tighter context window, which encourages the model to focus its limited capacity on the task.
B. Fast mode, which prioritizes the lowest possible latency at the expense of reasoning depth on complex tasks.
C. Zero-shot prompting alone with no model option adjustments, which keeps the application's configuration as simple as possible.
D. Extended thinking, which lets the model reason through the differential diagnosis steps before producing the final recommendation.

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. Increase the agent's timeout to several hours so that interruptions become rare enough to ignore in practice.
C. Run two copies of the agent in parallel for every task and use whichever one finishes first as the source of truth.
D. Restart the task from the beginning whenever a process is interrupted.

Question 4

A teammate has submitted a pull request that adds a Claude-powered feature to your service. The code works, but the prompt and model selection are hard-coded inline, error handling is missing, and there are no tests for the integration.
What would you request during code review?

A. Request changes that move prompt and model configuration to a configurable location and add tests, treating the missing error handling as a follow-up release item.
B. Approve the pull request and add the missing pieces yourself in a follow-up commit so the teammate can move on to other work immediately.
C. Request changes that move prompt and model configuration to a configurable location, add error handling for Claude API failures, and add tests for the integration.
D. Approve the pull request as-is, on the grounds that the feature works in the happy path and the missing pieces can be added in follow-up commits.

Question 5

The product team has asked you to choose a Claude model for a new feature. The team has provided functional requirements but has not specified performance, cost, or quality targets. The team's product manager says, "Use whatever model gives us the best results." How would you respond?

A. Choose the largest, highest-capability Claude model, on the grounds that "best results" is most likely to mean highest quality.
B. Ask the product team to specify quality, latency, and cost targets, then select the model whose tradeoffs best fit those targets.
C. Run every Claude model on a representative sample and pick whichever scores best on a generic benchmark.
D. Choose a mid-tier model and ship the feature, because mid-tier models work for most use cases without specified targets.

Solutions: