Instantly download CCAR-F updated real questions

Anthropic CCAR-F Exam Overview:

Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect - Foundations Sample Questions:

1. 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.
Your team frequently migrates React components to Vue. You've written a step-by-step workflow for Claude Code to follow during each migration, and you want every developer on the team to invoke it by typing
/migrate-component . The workflow should stay in sync as the team iterates on it.
Where should you place the skill file?

A) As a detailed instruction block in the project's root CLAUDE.md file.
B) In ~/.claude/skills/migrate-component/SKILL.md on each developer's machine.
C) In .claude/skills/migrate-component/SKILL.md at the project root, committed to version control.
D) In the project's .claude/settings.json using a skillOverrides entry to register and define the workflow.

2. You are building developer-productivity tools using the Claude Agent SDK. The agent helps engineers explore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automate repetitive tasks. It uses the built-in tools-Read, Write, Bash, Grep, and Glob-and integrates with Model Context Protocol (MCP) servers.
An engineer sees the unfamiliar error message SYNC_CONFLICT: entity version mismatch detected in production logs but does not know which of the 12 services in the codebase generates it. The engineer asks the agent to locate the responsible source code.
What exploration approach will find the responsible code most efficiently?

A) Use Grep to locate every file importing the project's error-handling module, and then read those files to find custom error definitions.
B) Read the project's README and service-configuration files, and then systematically read source files in every service directory.
C) Use Grep to search for distinctive text from the error message, such as SYNC_CONFLICT or entity version mismatch , and then read the matching files to understand the context.
D) Use Glob to find files in directories commonly associated with error handling, such as errors , exceptions , or handlers , and then read every matching file.

3. 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.
You need to add a date validation check ensuring event dates are in the future. This requires adding a conditional statement to one existing function in a single file.
What is the most appropriate approach?

A) Enter plan mode first to create a detailed implementation strategy before making the change.
B) Use direct execution to make the change.
C) Start with extended thinking mode enabled to ensure thorough reasoning about the validation logic.
D) Enter plan mode to analyze how the validation might impact other parts of the reservation flow.

4. 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 automated code review is missing genuine bugs in pull requests. Investigation reveals that your review prompt includes the instruction: "Only flag critical issues that would definitely cause production failures.
Ignore minor concerns and anything you are uncertain about." Developers confirm that some missed bugs are genuine logic errors that the model investigated but chose not to report. The team requires the review output to remain structured, with each finding tagged with metadata, and actionable.
Which prompt change both removes the cause of the suppressed findings and preserves structured, tagged output for downstream filtering?

A) Add a second review pass that rereads the diff using the same prompt, looking for anything the first pass may have missed.
B) Instruct the model to report all findings with confidence and severity tags, deferring filtering to a downstream step.
C) Enable extended thinking and instruct the model to reason step by step about every code change before producing its review.
D) Remove all severity-related instructions from the prompt and let the model use its default judgment about what to report.

5. You built an LLM-powered code-review tool that analyzes pull requests and returns structured findings. Each finding is a JSON object containing file_path, line_number, issue_category-such as security or style-and description. Developers can dismiss findings they consider unhelpful, and currently 35% of findings are dismissed. You want to analyze these dismissals to understand what the system is getting wrong and improve the prompts accordingly. What change to the output structure would best support this analysis?

A) Add a detected_pattern field recording the specific code construct that triggered the finding, such as single-letter loop variable.
B) Expand the description field with more detailed explanations of why each issue matters and how it should be fixed.
C) Remove the issue_category field and track dismissal rates only at the individual-finding level.
D) Add a model_confidence field from 0.0 to 1.0 and filter findings below a threshold calibrated against historical dismissal rates.

Solutions: