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Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect - Foundations Sample Questions:

Question 1

Your test-generation process produces unit tests for new code, but reviews show that 55% are low-value: trivial assertions that verify only that functions do not throw exceptions, tests that duplicate existing coverage, or tests that ignore your team's fixture conventions. How should you reduce the rate of low-value tests being generated in the first place?

A. Implement two-phase generation in which a second Claude call scores every test against quality criteria and filters out low-scoring tests before presenting them to developers.
B. Document your testing standards in CLAUDE.md, including valuable-test criteria, available fixtures and their intended uses, and examples distinguishing meaningful behavioural tests from trivial assertions.
C. Add post-generation coverage analysis that automatically filters out every generated test that does not increase line coverage beyond the existing test suite.
D. Restrict test generation to directories where historical quality metrics show higher acceptance rates, disabling it in areas where generated tests consistently require substantial editing.

Question 2

You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JavaScript Object Notation (JSON) schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.
Your extraction system implements automatic retries when validation fails. On each retry, the specific validation error is appended to the prompt. This retry-with-error-feedback approach resolves most failures within 2? attempts.
For which failure pattern would additional retries be LEAST effective?

A. The model extracts citation counts as locale-formatted strings ("1,234") when the schema requires integers.
B. The model extracts dates as ISO 8601 datetime strings ("2023-03-15T00:00:00Z") when the schema requires only the date portion (YYYY-MM-DD).
C. The model extracts keywords as a nested object organized by category when the schema requires a flat array of strings.
D. The model extracts "et al." for co-authors when the full list exists only in an external document not in the input.

Question 3

You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline. The system runs automated code reviews, generates test cases, and provides feedback on pull requests. You need to design prompts that provide actionable feedback and minimize false positives.
Your pipeline includes a release-notes generation step that classifies and summarizes approximately 200 commits at the end of each weekly release cycle. Each commit is currently sent as a separate Messages API request using a Sonnet-tier Claude model. The release notes are not needed until the following morning, providing approximately 12 hours of acceptable latency.
Your team must reduce the per-token API cost while retaining the same model, prompts, and output quality.
Which approach satisfies all these constraints?

A. Concatenate all 200 commit messages into one Messages API request because reducing the number of requests always reduces token costs.
B. Submit the 200 requests through the Message Batches API with unique custom_id values and retrieve the results after the batch finishes.
C. Replace the Sonnet-tier model with a Haiku-tier model to obtain a lower per-token price.
D. Issue the 200 Messages API requests concurrently because parallel execution reduces the per- token price.

Question 4

Your conversational assistant frequently generates multiple clarifying questions when users make ambiguous requests. When a user asks "Can you help me with the report?", the assistant responds: "I'd be happy to help! Could you tell me: 1) Which report? 2) What kind of help - drafting, reviewing, or formatting? 3) What's your deadline?" User analytics show a 40% conversation abandonment rate after these multi-question responses.
What's the most effective way to reduce friction while appropriately handling ambiguity?

A. Create a lookup table of common request patterns with predefined default interpretations, having the assistant respond with those defaults without stating the assumptions made.
B. Limit the assistant to one clarifying question per turn, using conversation history to accumulate answers over multiple exchanges rather than requesting everything upfront.
C. Modify the system prompt to instruct the assistant to make reasonable assumptions from available context, state those assumptions explicitly, and offer to adjust if the interpretation is wrong.
D. Add a preprocessing step using a smaller model to classify request ambiguity on a 1-5 scale, routing high-ambiguity requests to a clarification dialog and low-ambiguity requests directly to the assistant.

Question 5

You are using Claude Code to accelerate software development. Your team uses it for code generation, refactoring, debugging, and documentation. You need to integrate it into your development workflow with custom slash commands, CLAUDE.md configurations, and understand when to use plan mode vs direct execution.
A critical bug is affecting production users. Error logs show exceptions in the OrderProcessing module with a clear stack trace pointing to a specific function. You haven't worked with this module before. What's the most effective approach?

A. Use direct execution to examine the stack trace, read the relevant code, and implement a fix once you identify the root cause.
B. Use plan mode to analyze the error in context of the module's design, enumerate potential root causes, and prioritize fixes systematically.
C. Enter plan mode to explore the module's architecture and dependencies before attempting any fixes.
D. Start with direct execution to gather initial information, then switch to plan mode to design a comprehensive solution before implementing any changes.

Solutions: