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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 integrate with the Claude API directly or through a third-party abstraction layer that supports multiple LLM providers. The team has identified that all current and projected use cases run on Claude, no internal customer has requested LLM portability, and the team's product roadmap does not mention multi-provider support over the next two years. The third-party abstraction would add roughly 15 percent overhead in code complexity and introduce one additional dependency.
Which integration approach would you recommend?

A. Both integration paths in parallel, where the application uses each path on different runs to compare which performs better in production over time.
B. A custom multi-provider abstraction layer the team builds in-house so that the team controls every part of the abstraction the application uses for its API calls.
C. The third-party abstraction layer, on the grounds that multi-provider support is valuable for any application as a matter of long-term flexibility across vendors.
D. Direct integration with Claude through its SDK, because no multi-provider need exists and abstraction would add complexity that does not pay off.

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

Question 3

You are extending a Claude agent with a capability that needs to be reusable across multiple teams in the organization, with each team able to invoke and use it independently.
How would you build the capability?

A. As a wrapper around an existing built-in tool that adds the missing functionality, on the grounds that built-in tools cover the reuse pattern when extended carefully.
B. As a Skill or MCP server because both are purpose-built for cross-team reuse independently by each consuming team.
C. As a custom tool embedded in this team's agent only, with other teams able to copy the implementation into their own agents when they need the capability.
D. As a shared library that each team imports into its own Claude application code, with each team responsible for keeping the library up to date in its integration.

Question 4

Your team is debating how to manage the prompts used in your Claude application. Some prompts are checked into the code repository, some live in a separate configuration file, and some are constructed inline at runtime. The result is inconsistent, and a recent prompt change went out without code review.
What steps would you take?

A. Establish a single source of truth for prompts, version-control them alongside code, and require code review for prompt changes.
B. Move all prompts to inline runtime construction so the team can update them quickly through a streamlined process outside the standard code review workflow.
C. Move all prompts out of version control to a separate spreadsheet that team members can edit freely as the application evolves over time.
D. Establish a single source of truth for prompts but keep change review optional, allowing developers to update prompts directly when changes are urgent.

Question 5

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. Instruct Claude to return JSON sometimes and free text other times so the application's output captures both formats.
B. Include explicit constraints describing the required JSON schema and an instruction to produce only output matching that schema.
C. Omit any reference to the format and rely on a post-processing step in the application to reshape Claude's output.
D. Instruct Claude to use whichever output format it considers most appropriate for each request the application handles.

Solutions: