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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Output Evaluation and Validation | 21% | - Apply fact-checking and validation techniques - Edit and adapt outputs for the intended audience - Organize and curate information and select appropriate output formats - Identify hallucinations, inconsistencies, and biases in responses - Evaluate Claude-generated outputs for accuracy and completeness - Determine when human review or additional verification is required |
| Topic 2: Governance, Risk, and Responsible Use | 15% | - Apply data sensitivity, regulatory, and privacy considerations - Understand ethical implications of Claude use - Identify appropriate and inappropriate use cases - Follow organizational AI policies and governance standards |
| Topic 3: Workflow Integration and Solution Design | 16% | - Integrate Claude into existing workflows and communicate its value and limitations - Analyze requirements and use cases - Support solution design through iteration - Use Claude for research, planning, and process optimization |
| Topic 4: Product and Model Selection | 12% | - Manage context limitations and memory - Differentiate between Claude model types - Select appropriate Claude product features - Align model selection with task requirements |
| Topic 5: Prompting and Task Execution | 14% | - Adapt prompting strategy by task type - Apply task decomposition techniques to structure complex requests - Iterate prompts to improve output quality - Create effective prompts for business and technical tasks |
| Topic 6: Configuration and Knowledge Management | 12% | - Maintain and update configurations - Configure Claude Projects with instructions and knowledge sources - Create effective system-level instructions - Manage uploaded knowledge and connectors |
| Topic 7: Troubleshooting and Optimization | 10% | - Identify and diagnose issues with underperforming prompts or poor outputs - Adjust approaches based on feedback and results - Optimize workflows for efficiency and effectiveness |
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NEW QUESTION # 125
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: C,E
Explanation:
Under the objective Understand ethical implications of AI usage , evaluating HR workflows requires identifying systemic harms, legal compliance liabilities, and threats to employee rights.
Option A highlights the ethical danger of autonomous algorithmic decision-making: delegating high-stakes determinations (such as termination, performance ratings, or compensation) to an AI system without accountable human oversight violates fundamental fairness and labor ethics. Option E represents severe algorithmic bias and discrimination: generating outputs that systematically disadvantage candidates or employees based on protected characteristics (e.g., race, gender, age, disability). Both scenarios represent critical ethical risks. Conversely, minor clerical typos in calendar invites (Option B), formatting irregularities in general announcements (Option C), and punctuation style inconsistencies (Option D) are minor operational defects that carry zero ethical or regulatory consequences.
NEW QUESTION # 126
You are an HR specialist reviewing model choices made by colleagues for various tasks.
Which two model choices represent appropriate matches between the model and the task? (Select two.) Each correct answer presents a complete solution.
Answer: B,C
Explanation:
Under the objective Align model selection with task requirements (e.g., cost, speed, quality) , deploying models effectively requires matching model cognitive capacity to task complexity and throughput requirements.
Option C correctly routes complex, multi-layered tasks-such as synthesizing intricate legal precedents, statutory compliance, or multi-step policy analysis-to high-capability models (e.g., Claude 3 Opus or Sonnet) where deep reasoning is essential. Option E correctly routes simple, high-frequency, low-complexity tasks-such as standard FAQ lookups-to light, fast models (e.g., Claude 3 Haiku) to achieve ultra-low latency and minimal cost per request. Conversely, choosing models purely based on cost (Option A) is inefficient, deploying large frontier models for simple keyword extraction (Option B) wastes financial and rate-limit budgets, and assigning complex strategic synthesis across many documents to lightweight models (Option D) leads to shallow analysis and missed nuances.
NEW QUESTION # 127
You are a marketing manager using Claude to ideate concepts for a campaign and must complete the framing steps before generating concepts.
Which two framing steps must be completed BEFORE asking Claude to generate concepts? (Select two.) Each correct answer presents part of the solution.
Answer: A,B
Explanation:
Effective ideation requires a clear creative frame. Option A defines what the campaign is intended to achieve and how success will be assessed. Option D defines the intended audience and brand voice, ensuring that generated concepts are relevant to the people being addressed and consistent with the organization's identity.
Options B and C occur after concepts have been generated. A finalist cannot be selected or developed until candidate concepts exist. Option E concerns execution planning and should follow concept selection, validation, and approval. Scheduling does not provide the creative direction Claude needs during initial ideation.
A strong ideation prompt might specify the campaign objective, audience characteristics, brand attributes, channel, constraints, prohibited themes, desired number of concepts, and the dimensions along which the ideas should differ. Claude can then explore broadly within meaningful boundaries. Success metrics also create criteria for evaluating ideas after generation, preventing selection from being driven solely by subjective preference.
Anthropic's prompting guidance emphasizes providing clear context, objectives, audience information, and output expectations. For brainstorming, the framing should constrain relevance without prescribing the final answer so tightly that concept diversity is eliminated. Anthropic's prompting best practices
NEW QUESTION # 128
A senior project coordinator has been asked to use Claude to produce an end-of-year report covering finance, operations, and customer outcomes. The three areas have separate data owners and separate source documents.
Which decomposition approach is most likely to produce a strong report?
Answer: D
Explanation:
Under the objective Apply task decomposition techniques to structure complex requests , multi-domain deliverables requiring distinct data inputs demand modular, step-by-step composition.
Option A exemplifies best-practice task decomposition: first, establishing the overarching narrative and reporting goals; second, gathering and isolating domain-specific source material; third, executing dedicated, highly focused prompts to draft each detailed section (finance, operations, customer outcomes); and finally, feeding the finalized section drafts into Claude to synthesize a comprehensive, cohesive executive summary.
In contrast, drafting the executive summary before the underlying sections exist (Option B) forces the model to invent conclusions. Dumping all disparate documents into a single monolithic prompt (Option D) risks attention dilution and superficial analysis. Merely concatenating isolated outputs without an overarching executive synthesis (Option C) produces a disjointed final deliverable.
NEW QUESTION # 129
A knowledge worker is applying the AI Fluency Framework Description competency while revising an underperforming prompt.
Which revision best reflects Description principles?
Answer: C
Explanation:
Description concerns communicating a goal to AI with enough precision to produce useful behavior and an appropriate output. Option B strengthens the information that operationally defines success: the task's scope, intended audience, required format, and relevant constraints. These elements reduce the number of assumptions Claude must make.
Option A removes useful context and is likely to make the response more generic. Option C substitutes broad language for a defined specification, increasing ambiguity. Option D confuses prompt length with prompt quality. Additional words improve performance only when they convey relevant instructions, examples, source material, constraints, or decision criteria.
A strong revision might define the role Claude should perform, the source material it may use, exclusions, tone, length, required sections, and the purpose of the deliverable. The revised prompt should then be tested against clear criteria rather than assumed to be correct after one run.
Anthropic defines Description as effectively describing goals to prompt useful AI behavior and output. Its prompting guidance recommends clear, detailed instructions, relevant context, representative examples, and explicit output requirements. Therefore, B is the only revision that directly addresses the diagnosed specification gaps. Anthropic's AI Fluency framework
NEW QUESTION # 130
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