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| Section | Weight | Objectives |
|---|---|---|
| Applications and Integration | 33.1% | - Vision capabilities - Streaming and Batch API - Claude Messages API - SDK and third-party integration |
| Evaluation, Testing, and Debugging | 2.6% | - Error handling and debugging - Output evaluation and validation |
| Model Selection and Optimization | 16.8% | - Latency and performance trade-offs - Claude model family characteristics - Cost and token optimization |
| Tools and Model Context Protocol (MCP) | 10.6% | - Tool integration and usage - MCP server development |
| Security and Safety | 8.1% | - AI application security - Guardrails and safety controls |
| Prompt and Context Engineering | 11% | - Context window management - Prompt design and structuring - Structured output handling |
| Agents and Workflows | 14.7% | - Claude Agent SDK usage - Memory and context management - Workflow vs autonomous agents - Agent architecture principles |
| Claude Code | 3.1% | - Claude Code configuration and usage |
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NEW QUESTION # 54
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?
Answer: B
Explanation:
B is directly supported by both the supplied examination source and Claude Code's configuration model. The source marks the hierarchical CLAUDE.md approach as correct. Claude Code supports instructions at multiple scopes, allowing broadly applicable standards to be separated from project-specific context rather than duplicated across every repository.
Anthropic documents several CLAUDE.md scopes. Organization-managed instructions can apply broadly; user-level instructions in ~/.claude/CLAUDE.md apply across a user's projects; project instructions in .
/CLAUDE.md or ./.claude/CLAUDE.md provide repository-specific architecture, conventions, commands, and workflows. Claude Code loads applicable files according to the directory hierarchy, allowing broad instructions and more specific local instructions to coexist.
This arrangement improves maintainability because common coding standards are defined once at the appropriate scope, while each repository retains only the context unique to that project. A documentation website does not automatically inject rules into Claude Code context. C creates inconsistent manual configuration. D improperly couples unrelated repositories to one repository's configuration.
Relevant Claude Developer topics: Confia Management, CLAUDE.md hierarchy, organization scope, user scope, project scope, repository configuration, instruction inheritance, and configuration reuse .
NEW QUESTION # 55
A new agent your team built handles customer support tickets, but it routinely gets confused when a single ticket spans billing, shipping, and product issues. The agent often loses track of which sub-issue it has already addressed and revisits the same one. The team is considering architectural changes.
What architectural change would you recommend?
Answer: A
Explanation:
Option C applies an orchestrator-worker architecture to a request containing several distinct domains. Rather than making one agent continuously switch between billing, shipping, and product reasoning, an orchestrator can decompose the ticket, delegate each concern to an appropriately scoped specialist, track completion, and consolidate the resulting recommendations.
Anthropic describes this architecture directly: an orchestrator dynamically breaks down a task, delegates subtasks to worker agents, and synthesizes their results. Anthropic's multi-agent Research system similarly uses a lead agent that coordinates specialized subagents operating with independent contexts.
A rigid workflow is inappropriate because not every ticket contains the same combination or ordering of issues. B can improve behavior but leaves one agent responsible for managing all competing concerns and state. D increases raw context capacity without addressing decomposition or responsibility boundaries.
C is therefore the strongest architectural change when separate issue categories can be handled independently and then reconciled by a coordinating component. Relevant Study Guide topics: orchestrator-workers, subagents, delegation, task decomposition, context isolation, coordination, and synthesis.
NEW QUESTION # 56
Your application uses the Messages API to handle multi-turn conversations. Each new turn resends the entire conversation history, and your token costs are growing as conversations get longer. You suspect there is a more efficient approach.
How would you address this?
Answer: B
Explanation:
Option A is the technically verified answer. Anthropic documents that multi-turn agentic requests resend the growing conversation context on subsequent turns. Prompt caching allows repeated prompt prefixes-such as system instructions, tool definitions, and prior unchanged conversation content-to be reused at the lower cache-read rate rather than repeatedly charged as ordinary uncached input. Anthropic specifically identifies caching repeated context as a major production cost optimization.
B is incorrect even though the supplied PDF contains a duplicated screenshot in which B appears selected.
The Batch API is designed for asynchronous workloads that can tolerate delayed completion; it is not the appropriate mechanism for every interactive turn in a multi-turn conversation. Because the user requested verified answers rather than blindly reproducing marked selections, A is retained.
C discards potentially essential conversation state arbitrarily. D is a valid context-management technique in some long-running workflows, but summarizing after every turn creates additional model work and loses detail; it does not exploit repeated-prefix caching.
Therefore, A directly addresses the stated cost pattern while preserving conversation fidelity. Relevant Study Guide topics: Messages API, stateless conversation history, prompt caching, cached input tokens, multi-turn applications, token economics, and cost optimization.
NEW QUESTION # 57
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?
Answer: C
Explanation:
D follows the principle of choosing the simplest architecture that satisfies demonstrated requirements .
The supplied examination item explicitly marks D. In this scenario, portability is neither a present functional requirement nor a foreseeable roadmap requirement. Adding an abstraction therefore creates measurable complexity without delivering an identified product capability.
Anthropic provides official general-purpose SDKs for Claude in multiple languages. These expose the Messages API directly while adding idiomatic interfaces, type safety, streaming support, retries, and error handling. Anthropic separately describes compatibility layers and framework-specific libraries as alternative integration surfaces rather than requirements for ordinary Claude development.
A third-party abstraction becomes rational when there is a genuine requirement for multiple providers, vendor switching, standardized cross-model interfaces, or an existing architectural platform that mandates it. None exists here. Building that flexibility speculatively increases dependencies, debugging surface, version- compatibility work, and the possibility that provider-specific Claude capabilities are hidden behind a lowest- common-denominator API.
A optimizes for hypothetical future requirements. B doubles operational complexity. C creates an even larger maintenance burden.
Relevant Claude Developer topics: Claude App Design, SDK selection, abstraction boundaries, dependency management, YAGNI, integration architecture, and provider portability requirements .
NEW QUESTION # 58
You are setting up the configuration management approach for a new Claude Code project. Your team will use CLAUDE.md files and settings.json files to control behavior, and you want to make sure changes are tracked and reviewable.
The configuration management approach would...
Answer: B
Explanation:
D applies configuration as code and is the answer explicitly selected in the supplied examination source.
Claude Code treats project configuration as part of the repository's working context. Anthropic documents project-level CLAUDE.md as the mechanism for providing project instructions and context, while shared project configuration belongs in .claude/settings.json. Crucially, Anthropic states that .claude/settings.json is intended to be checked into source control and shared with the team .
Keeping these files alongside the code establishes a single versioned relationship between application behavior and the configuration that influences Claude Code. Standard pull requests then provide diffs, peer review, ownership controls, CI validation, audit history, and straightforward rollback. A particular commit can therefore reproduce both source code and its associated Claude project configuration.
A creates competing copies and synchronization risk. B artificially separates behavior configuration from the code version it affects. C creates the same problem specifically for settings.json.
Developer-local values remain distinct: .claude/settings.local.json exists specifically for settings that should not be committed.
Relevant Claude Developer topics: Confia Management, CLAUDE.md, settings.json, configuration as code, source control, pull-request review, reproducibility, auditability, and team-shared Claude Code configuration .
NEW QUESTION # 59
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