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| Section | Weight | Objectives |
|---|---|---|
| Tools and Model Context Protocol (MCP) | 10.6% | - MCP server development - Tool integration and usage |
| Claude Code | 3.1% | - Claude Code configuration and usage |
| Agents and Workflows | 14.7% | - Claude Agent SDK usage - Workflow vs autonomous agents - Agent architecture principles - Memory and context management |
| Security and Safety | 8.1% | - Guardrails and safety controls - AI application security |
| Evaluation, Testing, and Debugging | 2.6% | - Error handling and debugging - Output evaluation and validation |
| Model Selection and Optimization | 16.8% | - Claude model family characteristics - Cost and token optimization - Latency and performance trade-offs |
| Applications and Integration | 33.1% | - Streaming and Batch API - SDK and third-party integration - Claude Messages API - Vision capabilities |
| Prompt and Context Engineering | 11% | - Prompt design and structuring - Context window management - Structured output handling |
Question 1
The team is debating whether to integrate with the Claude API directly or through a third-party abstraction layer that supports multiple LLM providers. The team has identified that all current and projected use cases run on Claude, no internal customer has requested LLM portability, and the team's product roadmap does not mention multi-provider support over the next two years. The third-party abstraction would add roughly 15 percent overhead in code complexity and introduce one additional dependency.
Which integration approach would you recommend?
A. A custom multi-provider abstraction layer the team builds in-house so that the team controls every part of the abstraction the application uses for its API calls.
B. Direct integration with Claude through its SDK, because no multi-provider need exists and abstraction would add complexity that does not pay off.
C. Both integration paths in parallel, where the application uses each path on different runs to compare which performs better in production over time.
D. The third-party abstraction layer, on the grounds that multi-provider support is valuable for any application as a matter of long-term flexibility across vendors.
Question 2
Your Claude application is deployed to development, staging, and production environments. Each environment uses a different model version, different prompt versions, and different plugin dependencies, but the configuration is currently scattered across environment variables, hardcoded values, and undocumented setup scripts.
How would you manage the configuration?
A. Standardize all environments to use the same configuration values to eliminate the differences between development, staging, and production.
B. Consolidate the configuration into a version-controlled system documenting model version pinning, prompt versioning, and plugin dependencies for each environment.
C. Use the latest available model version everywhere and stop pinning model versions, on the grounds that pinning adds maintenance overhead the team should aim to reduce.
D. Move all configuration into hardcoded application code to reduce reliance on external configuration sources that are difficult to track over time.
Question 3
Your team uses Claude Code across multiple repositories. You want the team's rules and general coding standards to apply to all repositories, and other rules to apply only to specific repositories. The team is currently duplicating instructions across every repository's CLAUDE.md file.
How would you address this?
A. Use a CLAUDE.md hierarchy that scopes general standards broadly and project-specific context within each repository's local CLAUDE.md.
B. Use a single repository's CLAUDE.md as the central source of truth and link to it from every other repository's CLAUDE.md file.
C. Move all instructions to a separate documentation site that developers consult during Claude Code sessions across all repositories.
D. Stop using CLAUDE.md altogether and ask each developer to configure Claude Code manually for each project they work on.
Question 4
You are designing an agent that processes vendor invoices. The work involves a small number of well- understood steps, but occasionally an invoice arrives in an unexpected format that requires the system to decide between rerouting, requesting clarification, or flagging for human review.
The most appropriate architecture for this system is...
A. A workflow for the standard path with an agent invoked at the decision point for unexpected formats.
B. A manager agent that delegates each step of standard invoice processing to a dedicated subagent, with a separate subagent handling each unexpected format.
C. A fully autonomous agent that handles every invoice from start to finish across all formats.
D. A single large prompt that processes every incoming invoice, both standard and unexpected, in one model call.
Question 5
Your Claude application's content policy specifies categories of content it should not produce under any circumstance. The application currently has no mechanism to enforce this policy, and content matching these categories is appearing in the application's output.
How would you enforce the content policy?
A. Move enforcement to users by asking them to report content policy violations after the violating content has already reached them in the application's responses.
B. Enhance the system prompt to contain explicit instructions for the categories to avoid, complete with examples of each category. Treat the strengthened prompt as the primary enforcement mechanism for the application's content policy across all responses.
C. Remove the content policy entirely and let any output reach users during normal operation, accepting whatever content the application produces in response to incoming traffic.
D. Add deterministic output filtering that checks responses against the content policy before they reach users.
Solutions:
| Question 1 Answer: B | Question 2 Answer: B | Question 3 Answer: A | Question 4 Answer: A | Question 5 Answer: D |
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