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| Section | Weight | Objectives |
|---|---|---|
| Claude Models, Prompting & Context Engineering | 13% | - Prompt reuse and context engineering strategies - Context window optimization - Claude model selection and trade-offs - System prompts and prompt templates - Guardrails |
| Evaluation, Testing & Optimization | 16% | - Cost and performance optimization - Production monitoring and optimization - Evaluation metrics and datasets - System issue diagnosis - Evaluation framework design - A/B testing |
| Stakeholder Communication & Lifecycle Management | 14% | - Discovery and requirements gathering - Solution lifecycle management - Stakeholder management - Communicating architectural decisions - Architecture documentation - Service-level agreements |
| Governance, Safety & Risk Management | 14% | - Human-in-the-loop validation - Ethical AI considerations - Regulatory and compliance requirements - AI safety and guardrails - Security and risk management |
| Developer Productivity & Operational Enablement | 7% | - Developer enablement - Debugging and operational issue resolution - AI-assisted developer workflows - Claude tooling configuration for teams |
| Solution Design & Architecture | 17% | - Architectural patterns
- Decomposition techniques for complex problem solving - End-to-end architecture design - Multi-agent systems and orchestration - Alignment with business value, cost, performance, and SLAs |
| Integration | 19% | - RAG pipeline design
- Authentication and authorization analysis - Claude integration mechanisms
|
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NEW QUESTION # 40
You are designing the prompt for a ticket-triage classifier with thirty well-defined categories and clear category descriptions in the prompt.
Which technique is most appropriate as the starting point?
Answer: B
Explanation:
A clearly defined closed-set classification task should begin with a concise zero-shot prompt containing the permitted categories, unambiguous category descriptions, and the required output structure. This provides a simple, inexpensive baseline that can be measured against a representative evaluation set. Chain-of-thought prompting adds unnecessary latency and token usage when the routing decision does not require substantive multi-step reasoning. Permitting Claude to invent categories would violate the closed-set contract and complicate downstream automation. Omitting descriptions would increase ambiguity among potentially overlapping labels. If evaluation later reveals persistent confusion between particular categories, the architect can introduce targeted examples or refine the definitions. Prompt complexity should be added in response to measured failure patterns, not assumed to be necessary before establishing baseline performance. Anthropic:
Prompt engineering overview
NEW QUESTION # 41
You are defining transparency practices for a customer-facing assistant whose responses are materially shaped by AI.
Which transparency practice most directly supports responsible deployment?
Answer: B
Explanation:
Responsible deployment requires users to receive an accurate representation of the system with which they are interacting. Option C provides that transparency while also establishing a practical escalation path.
Disclosure should be proportionate to the material role AI plays, expressed in language appropriate to the audience, and aligned with organizational policy and applicable regulatory obligations.
A documented human-contact route is important when the assistant cannot resolve an issue, produces a disputed result, encounters a high-impact exception, or handles a matter requiring human authority. Anthropic' s Responsible Scaling Policy recognizes escalation to human reviewers as an appropriate safeguard for edge cases and situations requiring human judgment. Responsible Scaling Policy Options A and D intentionally conceal material AI involvement from affected users, weakening informed decision-making, auditability, and trust. Option B is also unsuitable because transparency does not require revealing proprietary prompts, confidential controls, or internal security mechanisms; however, it does require an honest explanation of AI involvement and the system's operational role.
The correct design combines disclosure, understandable limitations, human escalation, and records demonstrating that the organization's transparency requirements are consistently applied.
Study Guide references/topics: AI transparency; informed user interaction; human escalation; responsible deployment; disclosure policy; operational accountability.
NEW QUESTION # 42
You are selecting the documentation set that should accompany a Claude-based deployment at handoff.
Which set is most complete?
Answer: C
NEW QUESTION # 43
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.
Answer: A,D
NEW QUESTION # 44
A technical team is debating whether to implement a new capability for generating regulatory filings from internal data as a Claude Skill or as an MCP server. The capability requires a fixed authoring procedure with embedded examples, does not need to call live external systems, and must be portable across three Claude deployments: claude.ai, an internal API integration, and Claude Code.
Which factor most strongly favors implementing the capability as a Skill?
Answer: D
Explanation:
A Skill is the appropriate packaging mechanism for reusable procedural knowledge, instructions, templates, examples, and supporting resources. The filing capability follows a defined authoring method and requires no live external-system interaction, so an MCP server would introduce unnecessary transport, authentication, hosting, and operational complexity. MCP becomes appropriate when Claude must invoke live databases, APIs, or enterprise services. Command-line availability does not independently determine the design because Skills can be used across supported Claude environments. Direct identity-provider authentication would favor an integration or MCP service rather than a self-contained Skill. Anthropic describes Agent Skills as portable packages that provide agents with specialized procedural and organizational expertise. Agent Skills
NEW QUESTION # 45
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