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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

The product team has described a new Claude feature in business terms: "agents should help our analysts produce client memos faster." You need to convert this into actionable technical requirements for the engineering team.
Your first step would be to...

A. Examine what model capabilities and tier options are available and determine which best supports the memo drafting workflow described by the product team.
B. Interpret the functional and infrastructure requirements implied by the business goal.
C. Ask the analysts about the current memo production process to see where they think Claude could be introduced as a prompt-driven drafting step.
D. Assess what similar agent-based features have been built internally or in the industry and use those precedents to scope the technical approach.

Question 2

Your team's Claude application has been in production for a year, and the team has decided to formalize its testing strategy. Currently, the team writes ad-hoc tests for individual features but has no overall testing approach.
What testing approach would you formalize?

A. Adopt a test-driven development practice where unit tests are written before each feature is implemented and must pass before code is merged.
B. Define unit tests for individual functions, integration tests for the Claude integration, and end-to-end tests for critical user flows, applied consistently across the codebase.
C. Define a single testing approach that uses end-to-end tests and apply it consistently across all new features as they are added to the codebase.
D. Continue writing ad-hoc tests as features ship and introduce a peer review step to ensure each test adequately covers the feature being released.

Question 3

Your team uses Claude Code across multiple repositories. You want the team's rules and general coding standards to apply to all repositories, and other rules to apply only to specific repositories. The team is currently duplicating instructions across every repository's CLAUDE.md file.
How would you address this?

A. Use a single repository's CLAUDE.md as the central source of truth and link to it from every other repository's CLAUDE.md file.
B. Stop using CLAUDE.md altogether and ask each developer to configure Claude Code manually for each project they work on.
C. Move all instructions to a separate documentation site that developers consult during Claude Code sessions across all repositories.
D. Use a CLAUDE.md hierarchy that scopes general standards broadly and project-specific context within each repository's local CLAUDE.md.

Question 4

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

Question 5

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

Solutions: