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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prompting and Task Execution | 14% | - Adapting prompting strategies to task types - Task decomposition - Iterating prompts to improve output - Creating effective prompts |
| Topic 2: Governance, Risk, and Responsible Use | 15% | - Ethical and responsible AI use - Organizational AI governance and policies - Identifying appropriate and inappropriate AI use cases - Data sensitivity, privacy, and regulatory considerations |
| Topic 3: Product and Model Selection | 12% | - Managing context limitations and memory - Balancing quality, speed, and cost - Selecting appropriate Claude product features - Selecting Claude models |
| Topic 4: Troubleshooting and Optimization | 10% | - Diagnosing underperforming prompts and outputs - Optimizing workflows for efficiency and effectiveness - Adjusting approaches based on feedback and results |
| Topic 5: Workflow Integration and Solution Design | 16% | - Research, planning, and process optimization - Communicating Claude's value and limitations - Solution design and iteration - Analyzing requirements and use cases - Integrating Claude into existing workflows |
| Topic 6: Configuration and Knowledge Management | 12% | - Managing instructions and knowledge sources - Configuring Claude Projects - Maintaining configuration and knowledge sources - Managing uploaded knowledge and connectors |
| Topic 7: Output Evaluation and Validation | 21% | - Determining when human review or verification is required - Fact-checking and validation - Evaluating output accuracy and completeness - Identifying hallucinations, inconsistencies, and bias - Editing, adapting, and refining outputs |
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NEW QUESTION # 14
You are a knowledge worker preparing inputs for a Claude prompt.
Which data type most clearly requires extra handling such as redaction or anonymization before being included in the prompt?
Answer: C
Explanation:
Under the objective Apply data, privacy sensitivity, regulatory policies, and privacy considerations , enterprise data protection policies require strict tiering of data assets based on sensitivity and regulatory mandates (such as GDPR, PCI-DSS, and HIPAA).
Customer government identifiers (e.g., SSN, National Insurance number) combined with full payment card numbers and individual names (Option B) represent highly sensitive Personally Identifiable Information (PII) and protected financial data. Ingesting this data into AI prompts without masking, tokenization, or redaction introduces severe compliance violations and data privacy risks. In contrast, published corporate press releases (Option A), publicly accessible executive job titles (Option C), and public marketing product descriptions (Option D) are public information assets that require no anonymization or redaction before prompt inclusion.
NEW QUESTION # 15
A project manager is transforming a Claude-generated draft into a polished board memo. The board reads the memo before the meeting and expects it to be scannable, factually verified, and consistent with the organization's standard terminology.
Which set of refinements is most appropriate?
Answer: D
Explanation:
Under the objective Edit, adapt, refine, and compare the output generated by Claude model(s) for the intended audience (Domain 2: Output Evaluation and Validation), preparing deliverables for executive boards requires comprehensive structural, linguistic, and factual refinement.
Option A covers all four essential post-generation refinement criteria: applying standardized heading hierarchies for visual navigation, condensing prose to maximize executive scanability, aligning terminology with enterprise glossaries, and rigorously validating every metric and claim against primary source records.
Expanding narrative sections unnecessarily (Option B) reduces scanability for board members. Ignoring heading structure and vocabulary alignment (Option C) produces an unpolished deliverable. Relying blindly on the model's internal factual correctness without external verification (Option D) introduces governance and hallucination risks into board-level decisions.
NEW QUESTION # 16
You are sorting Claude output structural defects by which most undermines clarity.
Which structural defect most severely undermines the clarity of the output?
Answer: B
Explanation:
Under the objective Identify hallucinations, inconsistencies, and biases in responses , evaluating output quality requires distinguishing between cosmetic formatting imperfections and critical semantic contradictions.
A contradiction between the central conclusion and the supporting factual evidence in the body (Option D) represents a critical structural and logical breakdown. This defect directly destroys the internal consistency, credibility, and actionable utility of the deliverable, potentially misleading stakeholders and causing operational errors. In contrast, unequal subheading lengths (Option A), minor cosmetic typos (Option C), or slight terminology drift across paragraphs (Option B) represent surface-level stylistic flaws that can be quickly edited without fundamentally invalidating the underlying message of the artifact.
NEW QUESTION # 17
A senior manager is reviewing a colleague's habit of never updating their team's Project configurations because "if it works once, it works forever." Which feedback is most warranted?
Answer: D
Explanation:
Option C is correct because a Claude Project is a persistent workspace whose instructions and knowledge influence multiple chats. Anthropic explains that Project instructions tell Claude how to behave and respond across the Project, while uploaded knowledge is made available as context across its chats. Consequently, outdated policies, terminology, templates, or reference documents can systematically influence future outputs even when the degradation is not immediately obvious.
A sensible maintenance practice is to review the configuration periodically and whenever a meaningful source, policy, workflow, audience requirement, or organizational standard changes. Updates should then be tested against representative tasks and defined success criteria. Option A is too reactive because waiting for visible failure may allow inaccurate or obsolete outputs to circulate. Option B is incorrect because chat-level corrections do not reliably repair the persistent instructions or knowledge used in other Project chats. Option D is also too rigid: review can occur on a schedule, but changes should be evidence-based rather than made automatically when nothing relevant has changed.
Therefore, the best practice is controlled, periodic review combined with change-triggered maintenance and validation. This keeps the Project aligned without introducing unnecessary configuration churn. See Anthropic's guidance on creating and managing Projects and building evaluations .
NEW QUESTION # 18
You are a Claude associate troubleshooting a Claude response that introduces facts not present in the supplied source.
Which root cause is most directly indicated?
Answer: A
Explanation:
Answer D is correct. When Claude introduces facts that are absent from the supplied source, the most directly indicated prompt defect is the absence of an explicit grounding constraint. The prompt should clearly instruct Claude to use only the supplied material, avoid relying on external or general knowledge, and state when the source does not contain enough information. It can also require supporting quotations or citations for factual claims so that unsupported additions can be detected and removed.
Option A identifies a possible contributing factor, but asking for a comprehensive response does not inherently authorize invented information. A properly constrained comprehensive response can remain fully grounded in the source. Option B is incorrect because assigning a researcher role does not necessarily produce unsupported claims; the scope and permitted sources determine the behavior. Option C is also possible in a poorly designed template, but the presence of headings alone does not explain why Claude treats unsupported content as factual.
Anthropic specifically recommends external-knowledge restrictions, direct quotations, citations, and permission to acknowledge insufficient information when reducing hallucinations. Therefore, the missing source-only constraint is the clearest root cause and should be corrected first. Anthropic: Reduce hallucinations
NEW QUESTION # 19
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