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

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're implementing a new payment processing module that must follow your project's established patterns for database transactions, error handling, and audit logging. You've identified three existing modules that exemplify these patterns: db_utils.py , error_handlers.py , and audit_logger.py . This is a one-off integration task-these patterns are well-documented in your team wiki and don't need additional project-level documentation.
What's the most effective approach?

A) Use @ references to include the three modules directly in your prompt, giving Claude concrete code examples of the patterns to follow.
B) Describe the patterns from the three modules in natural language in your prompt, explaining the transaction handling approach, error format, and logging conventions Claude should follow.
C) Add documentation of each pattern to your CLAUDE.md file, establishing them as project conventions that Claude will apply automatically.
D) Ask Claude to explore your codebase to find and understand the transaction, error handling, and logging patterns before generating the new module.

3. 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) 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.
B) Search for the function name in project documentation to understand intended usage patterns and navigate to documented integration points.
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 search for the function's original name across the codebase.

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.
Testing reveals that when source documents are missing certain specifications, the model fabricates plausible- sounding values to satisfy your schema's required fields. For example, a document mentioning only dimensions receives a fabricated "weight: 2.3 kg" in the extraction output.
What schema design change most effectively addresses this hallucination behavior?

A) Change fields that may not exist in source documents from required to optional, allowing the model to omit them.
B) Add a "confidence" field alongside each specification where the model self-reports its certainty, then filter out low-confidence extractions.
C) Add explicit instructions to the prompt stating "only extract information explicitly stated in the document; use placeholder text for missing values."
D) Implement semantic validation that verifies each extracted value appears in or can be inferred from the source document text.

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

Solutions: