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| Section | Weight | Objectives |
|---|---|---|
| Output Evaluation and Validation | 21% | - Identify hallucinations, inconsistencies, and biases in responses - Determine when human review or additional verification is required - Edit and adapt outputs for the intended audience - Apply fact-checking and validation techniques - Evaluate Claude-generated outputs for accuracy and completeness - Organize and curate information and select appropriate output formats |
| Workflow Integration and Solution Design | 16% | - Support solution design through iteration - Analyze requirements and use cases - Integrate Claude into existing workflows and communicate its value and limitations - Use Claude for research, planning, and process optimization |
| Troubleshooting and Optimization | 10% | - Optimize workflows for efficiency and effectiveness - Adjust approaches based on feedback and results - Identify and diagnose issues with underperforming prompts or poor outputs |
| Configuration and Knowledge Management | 12% | - Configure Claude Projects with instructions and knowledge sources - Create effective system-level instructions - Manage uploaded knowledge and connectors - Maintain and update configurations |
| Product and Model Selection | 12% | - Manage context limitations and memory - Align model selection with task requirements - Select appropriate Claude product features - Differentiate between Claude model types |
| Prompting and Task Execution | 14% | - Iterate prompts to improve output quality - Adapt prompting strategy by task type - Apply task decomposition techniques to structure complex requests - Create effective prompts for business and technical tasks |
| Governance, Risk, and Responsible Use | 15% | - Understand ethical implications of Claude use - Identify appropriate and inappropriate use cases - Follow organizational AI policies and governance standards - Apply data sensitivity, regulatory, and privacy considerations |
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NEW QUESTION # 110
You are an HR specialist sorting potential ethical risks of a Claude-supported workflow.
Which two risks pose the highest ethical concern in an HR-adjacent workflow? (Select two.) Each correct answer presents a complete solution.
Answer: B,D
NEW QUESTION # 111
An HR team member is reviewing a Claude-drafted set of interview questions intended for use across all candidates for a single role. The questions will be asked in the same order to every candidate.
Which review practice best supports fairness?
Answer: A
Explanation:
Under the objective Understand ethical implications of AI usage , applying AI in human resources demands rigorous bias auditing to ensure fair, standardized, and legally defensible evaluation practices.
Structured interviewing requires that questions focus strictly on observable, job-related competencies and avoid implicit assumptions or biased phrasing that could systematically disadvantage candidates from diverse non-traditional backgrounds (Option A). Human review must verify that Claude-generated questions remain objective, relevant, and standardized across applicants. Assuming AI outputs are unbiased by default and checking only stylistic tone (Option B) introduces compliance and equity risks. Injecting unstructured, ad-hoc questions per candidate (Option C) or scrambling question order inconsistently (Option D) undermines standardization and equitable scoring across applicant pools.
NEW QUESTION # 112
You are evaluating whether a "redesign new-hire onboarding" request should be decomposed before prompting Claude.
Which feature of the request most strongly indicates decomposition will help?
Answer: A
Explanation:
Option B presents a compound assignment with three materially different deliverables: a process map, supporting content, and a measurement plan. Each requires different inputs, reasoning steps, evaluation criteria, and output structures. Decomposing the request allows the team to define the onboarding objective, map the current process, design the future-state workflow, draft the supporting materials, establish success measures, and then integrate the components into a coherent package.
Task decomposition improves control because each intermediate result can be reviewed before it becomes an input to the next stage. It also prevents one large prompt from underdeveloping a component, overlooking dependencies, or blending incompatible formats. For example, measurement criteria should be based on the redesigned process rather than generated independently before the workflow is defined.
Options A, C, and D describe familiar or narrowly bounded work that can reasonably be handled with one structured prompt. Anthropic's workflow guidance recommends breaking complex interactions into unique tasks and using prompt chains when additional structure is needed. Decomposition should therefore be driven by the number of distinct deliverables and their dependencies, not simply by the length of the request.
Anthropic's Claude workflow guidance
NEW QUESTION # 113
You are an operations lead integrating Claude into a multi-person team workflow.
Which integration step should be performed first?
Answer: A
Explanation:
Under the objective Integrate Claude into existing workflows to augment or redesign workflows , successful AI adoption requires structured process mapping prior to implementation, piloting, or scaling.
The foundational first step (Option A) is conducting task decomposition and interface analysis: analyzing the existing workflow to determine exact stages where Claude provides tangible leverage (e.g., synthesis, drafting, data categorization) versus stages that mandate human decision-making, verification, and sign-off (human-in-the-loop handoffs). Attempting to run a pilot (Option B), iterate based on pilot metrics (Option C), or author final training documentation (Option D) before defining the functional boundaries and handoff architecture results in unstructured trials, unclear accountability, and higher operational risk.
NEW QUESTION # 114
A strategy manager is reviewing a Claude-generated recommendation to consolidate the company's two regional warehouses into one. The recommendation cites three sources that estimate cost savings and one source confirming that consolidation is operationally feasible. Two source documents also contain estimates of one-time transition costs and a stakeholder concern about regional service levels, neither of which appears in the recommendation.
Which concern is most warranted?
Answer: A
Explanation:
Option D is correct because the recommendation is incomplete and directionally biased. Although its cited evidence may genuinely support consolidation, the omitted transition costs and service-level concern are material to the decision. Accuracy is not limited to whether included claims are supported; it also requires completeness, balanced use of the available evidence, and faithful treatment of factors that could alter the conclusion.
The recommendation should be re-prompted to incorporate the omitted evidence, quantify its effect where possible, explain unresolved uncertainty, and present counterarguments or risks alongside the projected savings. The revised output should then be checked against every relevant source. Anthropic recommends multidimensional evaluations aligned with the application's purpose, including task fidelity, relevance, context utilization, and other task-specific criteria. Its hallucination guidance also recommends citations and verification of claims against supporting source text.
Option A incorrectly treats material evidence as optional appendix content when it belongs in the core analysis. Option B invents an arbitrary source-count threshold; evidence quality and coverage matter more than a fixed number. Option C considers only confirmatory citations and ignores contradictory or qualifying information. Therefore, D identifies the central problem: selective evidence usage that could mislead stakeholders. See Anthropic's guidance on evaluating outputs and verifying claims with citations .
NEW QUESTION # 115
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