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Anthropic Claude Certified Architect - Foundations Sample Questions:

1. 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.
Your agent has analyzed a complex service module -reading 23 source files, tracing request flows, and identifying error handling patterns. A developer wants to compare two testing strategies before committing to one: end-to-end tests with mocked external services vs. snapshot tests capturing expected outputs. They need to independently develop both approaches to evaluate trade-offs. How should you manage the sessions?

A) Export the analysis session's key findings to a file, then create two new sessions that reference this file.
B) Continue in the original session, developing end-to-end tests first, then snapshot tests sequentially.
C) Start two fresh sessions, having each re-read the relevant source files before beginning.
D) Resume the analysis session with fork_session enabled, creating a separate branch for each testing strategy.

2. 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) Enter plan mode to analyze how the validation might impact other parts of the reservation flow.
C) Use direct execution to make the change.
D) Start with extended thinking mode enabled to ensure thorough reasoning about the validation logic.

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

4. Your track_shipment(tracking_id) tool queries an external logistics API that sometimes fails - the API may be temporarily unavailable, the tracking ID may be malformed, or the shipment may not exist. Currently, your tool raises a Python exception when errors occur. Users report the agent gives unhelpful responses like "I'm having trouble with that request" instead of suggesting alternatives such as verifying the tracking number format or checking by order number. How should you handle errors in tool results?

A) Create dedicated error-recovery tools (retry_tracking_lookup, search_by_order_number) that the model can invoke after the primary tracking tool returns a failure indicator.
B) Implement retry logic with exponential backoff inside the tool implementation so transient errors are automatically handled and only return a result after all retry attempts are exhausted.
C) Return structured error information as normal tool output including error type, recoverability status, and actionable context for the user.
D) Return a generic error response (e.g., {"success": false, "error": "lookup_failed"}) for all failure cases to maintain a consistent schema and avoid exposing internal error details.

5. Which practice MOST improves prompt maintainability?

A) Clearly separated sections with headings.
B) One paragraph containing all instructions.
C) Random ordering.
D) Minimal punctuation.

Solutions: