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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) Send a follow-up request including the validation error, asking the model to correct its output.
B) Implement a secondary pipeline using a larger model tier to reprocess documents that fail validation.
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 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 your agent to identify untested code paths in a legacy payment processing module spanning
45 files. After reading the first 8 source files, the agent's responses are becoming noticeably less accurate-it' s forgetting previously discussed code patterns and hasn't yet located all test files or traced critical payment flows.
What's the most effective approach to complete this investigation?

A) Clear context with /clear , then selectively re-read only the most critical files discovered so far, writing key findings to a scratchpad file that persists between context resets.
B) Document all current findings in a summary report, clear context completely, then use that report as the sole reference for continuing the investigation.
C) Spawn subagents to investigate specific questions (e.g., "find all test files for payment processing,"
"trace refund flow dependencies") while the main agent coordinates findings and preserves high-level understanding.
D) Switch to using Grep to search for specific function names instead of reading full files, reducing the content loaded into context for remaining exploration.

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're implementing a complex graph traversal algorithm with specific performance requirements and edge cases to handle (disconnected nodes, cycles, weighted edges). You want to structure your workflow for efficient iterative refinement with Claude.
What approach will most effectively enable progressive improvement across multiple iterations?

A) Write a test suite covering expected behavior, edge cases, and performance requirements before implementation. Ask Claude to write code that passes the tests, then iterate by sharing test failures with each refinement request.
B) Provide Claude with a detailed natural language specification of the algorithm, including all requirements and edge cases. Review each output manually and provide descriptive feedback on what behavior needs to change.
C) Provide Claude with a reference implementation from documentation, then ask it to rewrite the code to match your codebase style and add the required edge case handling, comparing outputs against the reference.
D) Have Claude extensively research the algorithm and create a detailed implementation plan using extended thinking, then implement the complete solution based on that plan.

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

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 your agent to add comprehensive tests to a legacy codebase with 200 files and minimal existing test coverage. The engineer hasn't specified which modules to prioritize.
How should the agent decompose this open-ended task?

A) Use Glob and Grep to map codebase structure, identify heavily-coupled modules, create a prioritized plan for high-impact areas, and revise as dependencies are discovered.
B) Systematically read all 200 files to create a complete function inventory before writing any tests, ensuring the testing plan accounts for every function before beginning.
C) Create a fixed testing schedule upfront based on directory structure, allocating equal effort to each top- level directory regardless of code complexity or business importance.
D) Start writing tests for the first module alphabetically, using test failures and imports to discover related files organically.

Solutions: