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| Section | Weight | Objectives |
|---|---|---|
| Stakeholder Communication & Lifecycle Management | 14% | - Manage stakeholder feedback and expectation alignment - Communicate architectural decisions and trade-offs - Document architectures and support full lifecycle phases - Conduct structured discovery and requirement gathering |
| Solution Design & Architecture | 17% | - Select architectural patterns: workflow, agentic, augmented LLM - Align solutions to business value pillars - Translate business problems into Claude-based AI solutions - Design end-to-end architectures and feedback loops - Design multi-agent systems and orchestration strategies |
| Claude Models, Prompting & Context Engineering | 13% | - Select appropriate Claude models based on trade-offs - Design system prompts, templates, and guardrails - Apply context engineering and context management techniques - Mitigate prompt injection, leaks, and jailbreak risks |
| 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 |
| Governance, Safety & Risk Management | 14% | - Ensure regulatory compliance (GDPR, HIPAA, etc.) - Address ethical AI considerations and bias mitigation - Implement guardrails and safety controls - Manage data privacy and security compliance |
| Integration | 19% | - Integrate Claude with enterprise systems, APIs, and tools - Implement Model Context Protocol (MCP) integrations - Integrate with data pipelines and RAG systems - Design authentication, authorization, and observability |
| Evaluation, Testing & Optimization | 16% | - Test accuracy, reliability, latency, and cost - Implement iterative improvement pipelines - Define evaluation metrics and success criteria - Optimize performance, prompting, and model selection |
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질문 # 104
The compliance team at a firm has approved a Claude Skill that generates client-facing investment summaries. The Skill includes the firm's required disclaimers and prohibited-language list. A product manager has asked whether additional guardrails are needed at the application layer or whether the Skill alone is sufficient.
Which two guardrail responsibilities should remain at the application layer rather than the Skill? (Select two.) Each correct answer presents part of the solution.
정답：C,E
설명：
Authorization and compliance logging must remain enforceable application-layer controls. Option B requires the application to authenticate the requester, resolve the user's role and entitlements, and deny the operation when the user lacks authority. A Skill can instruct Claude how to behave, but it is not a reliable security boundary and cannot replace identity-based access control enforced by the surrounding system.
Option A similarly belongs at the application layer. The application must create an authoritative audit event containing the requester, timestamp, Skill and model version, relevant input or content identifiers, generated output, review status, and retention classification. Audit evidence cannot depend on whether the model remembers or chooses to invoke a logging instruction.
Options C, D, and E describe reusable generation behavior that appropriately belongs within the approved Skill: house style, the standardized disclaimer, and the prohibited-language policy. The application may still validate their presence after generation, but the Skill remains the primary reusable content package.
The correct architecture separates behavioral guidance from deterministic enforcement. Skills supply domain instructions and templates; the application enforces identity, authorization, audit retention, data access, output validation, and consequential-action controls.
Study Guide references/topics: Skills versus application controls; authentication; authorization; compliance logging; deterministic guardrails; policy enforcement boundaries.
질문 # 105
You are evaluating a Claude-based deployment for adherence to a specific regulation.
Which two steps must be completed BEFORE mapping deployment data flows to specific regulatory clauses?
(Select two.)
Each correct answer presents part of the solution.
정답：B,C
설명：
Regulatory assessment must begin by establishing scope. Option B determines whether the regulation applies by examining processed data, affected jurisdictions, users, and deployment purpose. Without this analysis, clause mapping could apply irrelevant obligations or omit applicable ones. Option E establishes the platform's existing compliance capabilities, including audit records, retention controls, access governance, data residency, and compliance-export functionality. Anthropic's Trust Center provides control and certification information, while the Compliance API supports programmatic access to activity and governance records.
Options A and D occur after regulatory clauses have been mapped and gaps identified. Option C follows prioritization and approval of remediation actions.
Study Guide references/topics: Regulatory applicability; compliance affordance inventory; control mapping; gap assessment; residual risk; remediation sequencing.
질문 # 106
You are compiling continuity practices that span the deployment lifecycle.
Which two practices belong on the list? (Select two.)
Each correct answer presents a complete solution.
정답：A,C
설명：
Lifecycle continuity depends on preserving validated knowledge and feeding operational learning back into subsequent phases. Carrying the evaluation framework and reference set forward, as stated in Option B, creates a stable baseline across prompt changes, model migrations, retrieval adjustments, and architectural revisions. Rebuilding the evaluation system each time would undermine longitudinal comparison because changes in the test framework could be mistaken for changes in solution performance.
Option D establishes the second essential continuity mechanism: lessons from discovery, design, implementation, deployment, and production monitoring become explicit inputs to the next phase. This closes the feedback loop and prevents recurring defects, invalid assumptions, and operational findings from being lost at organizational handoffs.
Option A is overly mechanical. Stakeholders should receive communications relevant to their responsibilities and decision rights, not indiscriminate notifications at every transition. Option C confuses comprehensive archival with lifecycle continuity; retention must follow business, regulatory, security, and records- management requirements rather than an unconditional "archive everything" policy. Option E is directly contrary to iterative architecture. Decisions should be documented and governed, but material evidence or changed requirements must be allowed to reopen them.
Study Guide references/topics: Lifecycle phases; evaluation continuity; reference datasets; feedback loops; lessons learned; decision records; iterative architecture governance.
질문 # 107
You are operating an interactive assistant whose dominant performance constraint is per-turn latency. Quality on routine turns is already acceptable.
Which configuration adjustment most directly improves latency without disproportionately damaging quality?
정답：C
설명：
Option B targets two major contributors to per-turn latency: retrieved-context size and repeated prompt processing. Reducing retrieval to an empirically validated top- k limits the tokens Claude must process while preserving the passages that historically provide sufficient answer coverage. Caching the stable system- prompt prefix avoids repeatedly processing identical instructions.
Anthropic's latency guidance recommends choosing an appropriate model and reducing unnecessary input and output tokens. Its prompt-caching documentation explains that caching reusable prompt prefixes can reduce both repeated processing cost and latency. Reducing Latency , Prompt Caching The retrieval depth must be selected through evaluation rather than arbitrary truncation. The team should compare answer quality, retrieval recall, latency, and failure rates across candidate values and retain escalation logic for complex queries requiring deeper retrieval.
Option A removes an applicable latency optimization. Option C maximizes context consumption regardless of demonstrated benefit. Option D deliberately selects the slowest model class even though routine-turn quality already meets requirements.
Study Guide references/topics: Latency optimization; top- k retrieval; prompt caching; token reduction; quality-latency evaluation; adaptive retrieval.
질문 # 108
You are classifying chunking strategies by the corpus type each is best suited to.
For each chunking strategy, select the appropriate corpus type: "Long Structured Documents,"
"Heterogeneous Short Records," or "Code or Hierarchical Specifications."
정답：
설명：
Explanation:
* Function-level or section-level chunking for code modules - Code or Hierarchical Specifications
* Tree-aware chunking that follows code or specification hierarchy - Code or Hierarchical Specifications
* Per-record chunking where each record is one chunk - Heterogeneous Short Records
* Semantic chunking along clause or paragraph boundaries - Long Structured Documents
* Fixed-size chunking with overlap for short records of similar length - Heterogeneous Short Records
* Hierarchical chunking that mirrors document section structure - Long Structured Documents Chunking must preserve the structural unit that carries meaning in the source corpus. Code and hierarchical specifications are best divided at function, module, class, or tree boundaries because arbitrary token cuts can separate definitions from their implementation or parent context. Heterogeneous short-record collections should generally preserve each record as an independent chunk. Fixed-size overlapping chunks are also effective when records have broadly similar lengths and lack meaningful internal hierarchy. Long structured documents benefit from semantic boundaries such as clauses and paragraphs, while hierarchical chunking preserves relationships among sections, subsections, and parent headings. Anthropic notes that chunk size, boundaries, and overlap materially affect retrieval performance; therefore, one universal chunking method is inappropriate. Anthropic Contextual Retrieval
질문 # 109
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