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Anthropic Claude Certified Architect – Foundations Sample Questions:

1. 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.
Monitoring shows 12% of extractions fail Pydantic validation with specific errors like "expected float for quantity, got '2 to 3'". Retrying these requests without modification produces identical failures.
What's the most effective approach to recover from these validation failures?

A) Implement a secondary pipeline using a larger model tier to reprocess documents that fail validation.
B) Send a follow-up request including the validation error, asking the model to correct its output.
C) Set temperature to 0 to eliminate output variability and ensure consistent formatting.
D) Pre-process source documents to standardize problematic formats before sending them for extraction.

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.
A security audit requires updating your authentication library from v2 to v3. The migration guide documents breaking changes: authenticate() now returns a Promise instead of accepting a callback, the User type has restructured fields, and three deprecated methods were removed. Grep shows the library is imported in 45 files across several modules.
What's the most effective approach?

A) Paste the migration guide's breaking changes into your prompt and use direct execution to update all usages across the 45 files.
B) Update the dependency version, run the test suite, and use Claude Code to fix each failure as it appears.
C) Create a custom slash command encapsulating the migration transformations, then execute it against each file without prior codebase exploration.
D) Enter plan mode to explore library usage across modules, map affected code paths, then create a migration strategy before implementing.

3. You are building a customer support resolution agent using the Claude Agent SDK. The agent handles high- ambiguity requests like returns, billing disputes, and account issues. It has access to your backend systems through custom Model Context Protocol (MCP) tools ( get_customer , lookup_order , process_refund , escalate_to_human ). Your target is 80%+ first-contact resolution while knowing when to escalate.
Compliance requires that refunds exceeding $500 must automatically escalate to a human agent-this rule cannot be left to model discretion. Despite clear system prompt instructions, production logs show the agent occasionally processes high-value refunds directly (3% failure rate).
How should you achieve guaranteed compliance?

A) Strengthen the system prompt with emphatic language: "CRITICAL POLICY: Refunds over $500 MUST trigger human escalation. NEVER process these directly."
B) Implement a hook to intercept tool calls, when the refund process amount exceeds $500, block it and invoke human escalation.
C) Add few-shot examples to the prompt showing correct escalation behavior at various refund amounts ($400, $500, $600).
D) Modify the refund tool to return an error with message "Amount exceeds policy limit-please escalate" when the threshold is exceeded.

4. 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 submits two requests:
* Request A: "Rename the getUserData function to fetchUserProfile everywhere it's used."
* Request B: "Improve error handling throughout the data processing module-add try/catch blocks, meaningful error messages, and ensure failures don't silently corrupt data." For which request does specifying an explicit multi-phase workflow (such as analyze # propose # implement with review) most improve outcome quality?

A) Neither request benefits significantly
B) Request B, the error handling task
C) Request A, the function rename task
D) Both requests benefit equally

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 find all callers of a function before removing it. The function is defined in a core library but is also exposed through wrapper modules that rename the function for domain-specific use (e.
g., calculateTax in the library becomes computeOrderTax in the orders module).
What exploration strategy will most reliably identify all callers?

A) Search for the function name in project documentation to understand intended usage patterns and navigate to documented integration points.
B) Use Grep to search for the function's original name across the codebase.
C) Read the library and wrapper modules to identify all exposed names for the function, then Grep for each name across the codebase.
D) Use Grep to find all files that import from the library or wrapper modules, then read each file to check whether it uses the function.

Solutions: