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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Evaluation, Testing & Optimization | 16% | - Implement iterative improvement pipelines - Optimize performance, prompting, and model selection - Test accuracy, reliability, latency, and cost - Define evaluation metrics and success criteria |
| Topic 2: Solution Design & Architecture | 17% | - Align solutions to business value pillars - Design end-to-end architectures and feedback loops - Select architectural patterns: workflow, agentic, augmented LLM - Translate business problems into Claude-based AI solutions - Design multi-agent systems and orchestration strategies |
| Topic 3: Integration | 19% | - Design authentication, authorization, and observability - Implement Model Context Protocol (MCP) integrations - Integrate Claude with enterprise systems, APIs, and tools - Integrate with data pipelines and RAG systems |
| Topic 4: Stakeholder Communication & Lifecycle Management | 14% | - Document architectures and support full lifecycle phases - Conduct structured discovery and requirement gathering - Communicate architectural decisions and trade-offs - Manage stakeholder feedback and expectation alignment |
| Topic 5: Governance, Safety & Risk Management | 14% | - Implement guardrails and safety controls - Address ethical AI considerations and bias mitigation - Ensure regulatory compliance (GDPR, HIPAA, etc.) - Manage data privacy and security compliance |
| Topic 6: Claude Models, Prompting & Context Engineering | 13% | - Design system prompts, templates, and guardrails - Select appropriate Claude models based on trade-offs - Mitigate prompt injection, leaks, and jailbreak risks - Apply context engineering and context management techniques |
| Topic 7: Developer Productivity & Operational Enablement | 7% | - Support debugging, monitoring, and operational resolution - Improve developer workflows with AI-assisted tooling - Configure Claude tools and environments for teams |
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46. Frage
You are a solution architect evaluating candidate use cases for a Claude-based program.
For each scenario, select Yes if Claude is appropriate as the primary solution at the architectural level.
Otherwise, select No.
Antwort:
Begründung:
Explanation:
* Drafting first-pass investigative reports from semi-structured incident logs for analyst review - Yes
* Computing real-time fraud scores at sub-50-millisecond latency on a streaming pipeline - No
* Long-context contract review with structured clause extraction and deviation flagging - Yes
* Replacing a vector index for semantic retrieval over a multi-million-document corpus - No
* Routing inbound support tickets into 30 categories with reasoning for the selected route - Yes Claude is well suited to language-intensive analysis, summarization, extraction, classification, and drafting.
Investigative-report drafting, contract analysis, and support-ticket routing all require interpretation of unstructured or semi-structured language and can incorporate human review. A sub-50-millisecond fraud- scoring path requires deterministic, specialized real-time processing and should not place LLM inference on the critical path. Claude also does not replace the retrieval index used to search millions of documents; it consumes the results produced by that infrastructure. The correct architectural decision separates tasks requiring semantic language reasoning from deterministic computation and information-retrieval infrastructure. Model selection and evaluation must then confirm that the chosen Claude model satisfies quality, latency, and cost requirements.
47. Frage
A team manager wants all engineers working on the same repository to share identical MCP server definitions without manual synchronization.
Which configuration approach satisfies this requirement?
Antwort: B
Begründung:
Project-scoped configuration is the appropriate mechanism for repository-specific settings that must remain consistent across collaborators. Claude Code recognizes `.claude/settings.json` as the shared project settings file and `.mcp.json` as the project-level MCP server configuration. When these files are committed to source control, every engineer receives the same definitions through the repository's normal clone, pull, review, and versioning workflow.
Anthropic's scope hierarchy distinguishes project configuration from user and local configuration. Files under the user scope apply to one engineer and are not automatically shared. Operating-system environment variables are also workstation-specific and require separate configuration management. Managed settings can be distributed centrally, but they are primarily intended for organization-wide security policies and controls that must be enforced by administrators; they are less appropriate when the configuration belongs specifically to one repository.
Shared configuration should contain server definitions and environment-variable references, but not plaintext credentials. Each engineer can resolve required secrets through an approved local secret mechanism while retaining identical server names, transports, arguments, and non-sensitive settings. Project MCP servers also remain subject to workspace trust and approval controls before execution.
Study Guide references/topics: [Claude Code configuration scopes](https://docs.anthropic.com/en/docs
/claude-code/settings); project-scoped MCP servers; `.mcp.json`; repository-based operational standardization; secure secret separation.
48. Frage
You are running a risk assessment on a planned Claude-based deployment and must complete the inventory steps before assessing threats against assets.
Which two steps must be completed BEFORE assessing threats against assets to estimate likelihood and impact? (Select two.) Each correct answer presents part of the solution.
Antwort: C,D
Begründung:
Threat assessment requires an inventory of what must be protected and who or what may threaten it. Asset identification should cover prompts, retrieved documents, credentials, model outputs, audit logs, tools, external systems, and sensitive business or personal data. Sensitivity classifications establish the potential confidentiality, integrity, safety, and availability impact of compromise. Threat actors and attack vectors must then be enumerated so likelihood and impact can be assessed against specific assets. Mitigation recommendations, residual-risk acceptance, ownership, and final documentation follow the analysis; they cannot be completed coherently before the threats are understood. Anthropic's security transparency materials similarly emphasize maintaining threat models that reflect relevant attacker tactics and techniques. Anthropic Transparency Hub
49. Frage
You are defining an SLA for a Claude-based assistant.
Which SLA definition is most operationally meaningful?
Antwort: D
Begründung:
An operational SLA must be objectively measurable and enforceable. Option B defines the metric, percentile, threshold, and observation window, allowing both parties to determine whether service performance complied with the agreement. A complete SLA also defines what follows a breach, such as escalation, remediation, service credits, capacity changes, or architectural review. Percentile latency is preferable to an average because it exposes degraded tail performance experienced by a meaningful portion of users. Anthropic provides usage, cost, and operational data that can support monitoring and alerting through the Usage and Cost API . Options A and C are subjective. Option D remains incomplete because neither assessment periods nor breach handling can be applied consistently.
Study Guide references/topics: SLA construction; p95 latency; thresholds; evaluation windows; breach consequences; operational measurement.
50. Frage
You are integrating Claude Code into a workflow that runs against a production database.
Which guardrail design most directly preserves safety on data-modifying operations?
Antwort: D
Begründung:
Option D applies three complementary controls. First, a read-only database credential creates an authorization boundary outside the model; prompt instructions alone cannot convert that credential into write access.
Second, restricting the subagent's tool list reduces capability exposure by preventing the agent from selecting unrelated or unnecessarily privileged operations. Third, explicit human confirmation creates a deliberate approval gate before any exceptional data-changing action is executed.
This is defense in depth. If Claude misinterprets a request or processes malicious instructions from untrusted content, the restricted credential and tool configuration limit the available action surface. Human review then protects operations with potentially irreversible production consequences. Logging and audit trails should remain enabled to record the actor, request, tool call, approval, affected records, and outcome.
Anthropic documents that Claude Code begins with read-only permissions in Manual mode and requests approval for actions that modify the environment. Its permission system also supports granular allow, ask, and deny controls for MCP tools and subagents. Claude Code Security , Configure Permissions Options A and B eliminate least privilege and approval boundaries. Option C removes essential detection and forensic evidence.
Study Guide references/topics: Production database safety; least privilege; read-only defaults; MCP permissions; subagent scoping; human confirmation; auditability.
51. Frage
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