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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Evaluation, Testing, and Debugging | 2.6% | - Error handling and debugging - Output evaluation and validation |
| Topic 2: Model Selection and Optimization | 16.8% | - Cost and token optimization - Claude model family characteristics - Latency and performance trade-offs |
| Topic 3: Applications and Integration | 33.1% | - Vision capabilities - Streaming and Batch API - Claude Messages API - SDK and third-party integration |
| Topic 4: Prompt and Context Engineering | 11% | - Context window management - Prompt design and structuring - Structured output handling |
| Topic 5: Tools and Model Context Protocol (MCP) | 10.6% | - Tool integration and usage - MCP server development |
| Topic 6: Claude Code | 3.1% | - Claude Code configuration and usage |
| Topic 7: Security and Safety | 8.1% | - AI application security - Guardrails and safety controls |
| Topic 8: Agents and Workflows | 14.7% | - Agent architecture principles - Claude Agent SDK usage - Memory and context management - Workflow vs autonomous agents |
Question 1
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. 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.
B. Standardize all environments to use the same configuration values to eliminate the differences between development, staging, and production.
C. Move all configuration into hardcoded application code to reduce reliance on external configuration sources that are difficult to track over time.
D. Consolidate the configuration into a version-controlled system documenting model version pinning, prompt versioning, and plugin dependencies for each environment.
Question 2
Your Claude application's outputs are inconsistent in format. The team's instructions are scattered across the system prompt and user messages, with some instructions stated only once and others repeated.
How would you fix the inconsistency?
A. Repeat all instructions in both the system prompt and the user message so the model sees each instruction more than once.
B. Place each instruction wherever the developer who first wrote it found most natural, retaining the original intent.
C. Consolidate behavioral and format instructions in the system prompt and keep user messages focused on the user's input.
D. Move all instructions into the user message so the application's behavior is controlled at the input point.
Question 3
Your enterprise has a contract with AWS that requires Claude API calls to flow through Amazon Bedrock rather than the direct Anthropic API. Your team is building a new Claude application and is unfamiliar with this constraint.
How would you build the application?
A. Build the application against the direct Anthropic API and ignore the contractual requirement to route Claude calls through Amazon Bedrock.
B. Build the application against the direct Anthropic API now and migrate to Bedrock in a follow-up release once the team has more experience with the Bedrock API.
C. Build two parallel implementations of every call, one for the direct Anthropic API and one for Bedrock, and pick the faster one at runtime.
D. Configure the application to invoke Claude through the Bedrock-compatible API path while keeping the application's logic provider-agnostic.
Question 4
You are setting up a CI/CD pipeline for a new Claude application. The pipeline needs to run automated checks on every pull request before code can be merged.
The CI/CD checks would include...
A. Automated linting and security scanning, with Claude integration testing handled manually during pre- release verification by a designated reviewer.
B. A full end-to-end production deployment on every pull request to catch all possible issues before any code is merged into the main branch.
C. Automated tests of the Claude integration only, with linting handled separately during local development on each developer's machine.
D. Automated tests of the Claude integration, linting, and any other standard quality gates the team applies to its other services.
Question 5
You are designing an agent that handles a multi-step research task. You want the agent to break the task into smaller pieces, hand each piece to a focused subagent, and consolidate the results.
The agent pattern you would apply is...
A. An orchestrator and subagent pattern with specialized subagents assigned to each subtask.
B. A memory pattern that stores the entire research history in advance, before any subtask begins execution.
C. A single tool-use loop that includes every tool the agent might need across all subtasks.
D. A context-window pruning pattern that drops each subtask's content after the agent moves on.
Solutions:
| Question 1 Answer: D | Question 2 Answer: C | Question 3 Answer: D | Question 4 Answer: D | Question 5 Answer: A |
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