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Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect - Foundations Sample Questions:

Question 1

A company is building its first production Claude application. Which principle should guide the initial deployment?

A. Start with a simple design and iteratively evaluate improvements.
B. Disable monitoring to reduce costs.
C. Optimize only for response speed.
D. Maximize prompt complexity immediately.

Question 2

A healthcare company processes long clinical reports. Some exceed Claude's practical context requirements. What is the BEST architectural approach?

A. Increase temperature.
B. Randomly remove paragraphs.
C. Chunk documents before processing.
D. Ignore the excess text.

Question 3

You are building a multi-agent research system using the Claude Agent SDK. A coordinator agent delegates to specialized subagents: one searches the web, one analyzes documents, one synthesizes findings, and one generates reports. The system researches topics and produces comprehensive, cited reports.
Production monitoring shows that the research phase takes longer than expected. Analysis reveals that the coordinator invokes the web-search subagent, waits for its response, and then invokes the document-analysis subagent. These tasks are independent; neither requires the other's output.
How should you modify the system to run these subagents concurrently?

A. Switch both subagents to a Haiku-tier model instead of Sonnet to reduce their individual execution times.
B. Structure the coordinator to emit both Agent tool calls--formerly Task tool calls--in a single response rather than across separate conversation turns.
C. Create an asynchronous orchestration layer that starts separate coordinator-subagent pairs in parallel and aggregates their results.
D. Add instructions explaining the performance benefits of parallel execution and requesting that the coordinator invoke both subagents simultaneously.

Question 4

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 system extracts event metadata (date, location, organizer, attendee_count) from news articles using a JSON schema with all nullable fields. During evaluation, you observe the model frequently generates plausible but incorrect values for fields not mentioned in the article--for example, outputting "500" for attendee_count when the source contains no attendance information.
What's the most effective way to reduce these false extractions?

A. Upgrade to a more capable model tier with improved instruction-following to reduce hallucination tendencies.
B. Add a post-processing step using a second LLM call to verify each extracted value exists in the source document.
C. Add prompt instructions to return null for any field where information is not directly stated in the source.
D. Make all schema fields required (non-nullable) with strict validation rules to ensure the model only outputs verifiable data.

Question 5

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, Glob) and integrates with Model Context Protocol (MCP) servers.
An engineer asks the agent to understand how the caching layer works before adding a new cache invalidation trigger. After initial Grep searches, the agent has identified that caching logic spans 15 files including decorators, middleware, and service classes (~8,000 lines total). What's the most effective next step for building understanding while managing context constraints?

A. Use Glob to find files matching common caching patterns (cache.py, caching/), prioritize the largest files by reading them first, then check smaller files for gaps.
B. Use the Read tool to sequentially load all 15 files, building complete understanding across the full caching implementation.
C. Analyze imports and class hierarchies to identify the base cache class, Read that file to understand the interface, then trace specific invalidation implementations.
D. Use Grep to search for "invalidate" and "expire" patterns across all files, then Read only those specific line ranges with minimal surrounding context.

Solutions: