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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prompting and Task Execution | 14% | - Apply task decomposition techniques to structure complex requests - Iterate prompts to improve output quality - Adapt prompting strategy by task type - Create effective prompts for business and technical tasks |
| Topic 2: Output Evaluation and Validation | 21% | - Apply fact-checking and validation techniques - Organize and curate information and select appropriate output formats - Determine when human review or additional verification is required - Identify hallucinations, inconsistencies, and biases in responses - Evaluate Claude-generated outputs for accuracy and completeness - Edit and adapt outputs for the intended audience |
| Topic 3: Troubleshooting and Optimization | 10% | - Adjust approaches based on feedback and results - Optimize workflows for efficiency and effectiveness - Identify and diagnose issues with underperforming prompts or poor outputs |
| Topic 4: Product and Model Selection | 12% | - Align model selection with task requirements - Select appropriate Claude product features - Differentiate between Claude model types - Manage context limitations and memory |
| Topic 5: Governance, Risk, and Responsible Use | 15% | - Apply data sensitivity, regulatory, and privacy considerations - Follow organizational AI policies and governance standards - Identify appropriate and inappropriate use cases - Understand ethical implications of Claude use |
| Topic 6: Workflow Integration and Solution Design | 16% | - Support solution design through iteration - Integrate Claude into existing workflows and communicate its value and limitations - Use Claude for research, planning, and process optimization - Analyze requirements and use cases |
| Topic 7: Configuration and Knowledge Management | 12% | - Manage uploaded knowledge and connectors - Configure Claude Projects with instructions and knowledge sources - Create effective system-level instructions - Maintain and update configurations |
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NEW QUESTION # 23
An account manager has used Claude to extract requirements from stakeholder notes. Three requirements appear to conflict: two stakeholders specified mutually exclusive workflow steps, and a third requirement assumes an outcome that the first two would prevent.
Which step is most appropriate?
Answer: D
Explanation:
Option C is correct because Claude can identify and organize conflicting requirements, but it does not possess the authority or stakeholder context required to resolve substantive business disagreements independently.
Each conflicting requirement should be retained, labelled with its originating source, and marked with an unresolved status. The relevant stakeholders can then clarify priorities, negotiate trade-offs, or provide an authoritative decision.
Option A delays a known dependency and risks allowing downstream design work to proceed on incompatible assumptions. Option B permits Claude to invent compromise language that may not represent any stakeholder's actual position. Claude may help draft possible resolution questions, but those proposals must not be treated as approved requirements. Option D is equally inappropriate because apparent business justification in meeting notes does not grant the account manager or Claude authority to discard competing requirements.
Anthropic's hallucination guidance recommends grounding claims in supplied evidence and making outputs auditable with citations. Its AI Fluency Discernment principles also require humans to evaluate outputs critically and retain final judgment. Source traceability and stakeholder escalation therefore provide the most reliable resolution path. See Anthropic's guidance on reducing hallucinations and the AI Fluency Framework .
NEW QUESTION # 24
You are reviewing colleagues' responses to feedback received on Claude-drafted communications.
Which two feedback responses are productive? (Select two.)
Each correct answer presents a complete solution.
Answer: B,E
Explanation:
Options C and D are correct because productive feedback handling requires clarification, traceability, and controlled revision. When feedback is ambiguous, the writer should confirm the reviewer's intent before changing the draft. Otherwise, an incorrect interpretation may introduce new problems or remove content the reviewer intended to preserve.
Mapping each feedback item to a specific revision creates an auditable record showing what changed and why. It also helps identify unresolved comments, conflicting requests, and recommendations that were deliberately declined. This approach supports systematic comparison between the original and revised outputs.
Option A is inappropriate because contradictory suggestions cannot always be implemented simultaneously; the conflict must first be resolved by the appropriate reviewer or decision-maker. Option B postpones potentially material corrections without justification. Option E incorrectly assumes that Claude-generated text deserves automatic acceptance. Claude's output must be evaluated using the same professional, factual, and audience-specific standards applied to human-created content.
Anthropic's Description-Discernment process recommends assessing Claude's output, providing specific feedback, requesting targeted revisions, and applying human expertise and judgment to the final result.
Therefore, clarification and feedback-to-change traceability are the two productive responses. See Anthropic's Description-Discernment Loop and evaluation guidance .
NEW QUESTION # 25
A finance manager must select a Claude feature for a task that requires deterministic calculations across a multi-tab spreadsheet.
Which selection best fits the requirement?
Answer: B
Explanation:
Code Execution is the appropriate feature because it can run Python or shell-based computation in a sandboxed environment, process uploaded files, perform complex calculations, and generate analytical outputs. For a multi-tab spreadsheet, Claude can use code to read each worksheet, apply defined formulas or transformation logic, reconcile values, and return results that can be reproduced and inspected.
A normal chat response can describe calculations but does not necessarily execute them. Research mode is designed to gather and synthesize information from sources rather than serve as the primary calculation engine for an uploaded workbook. An Artifact can display or preserve an output, but the Artifact surface alone is not the computational mechanism.
Code execution improves reproducibility, but it does not guarantee that the formulas, assumptions, or source data are correct. The finance manager must review the generated code, validate important totals against known values, test edge cases, and reconcile outputs with the workbook's business rules. Anthropic's documentation explicitly states that Code Execution can analyze data, process uploaded files, perform complex calculations, and create visualizations in a secure sandbox. Therefore, D is the only feature selection aligned with deterministic spreadsheet computation. Anthropic's Code Execution documentation
NEW QUESTION # 26
A learning specialist is configuring a Claude Project for a recurring course-design workflow.
Which configuration approach best leverages a Skill alongside other Project elements?
Answer: A
Explanation:
Under the objective Configure Claude Projects with instructions and knowledge sources (Domain 5:
Configuration and Knowledge Management), maximizing the utility of Claude Projects involves harmonizing all built-in platform capabilities: custom instructions, knowledge bases, and specialized Skills.
Option B exemplifies an integrated configuration: packaging procedural execution logic into a Project Skill, uploading pedagogical frameworks and curriculum standards to Project knowledge, and authoring system instructions that explicitly define how Claude should utilize the Skill in conjunction with the knowledge repository. In contrast, creating contradictory instructions (Option A) causes prompt collisions and erratic behavior. Disabling skills (Option C) forces repetitive manual prompt engineering in every chat. Omitting supporting reference knowledge and system instructions (Option D) leaves the Project ungrounded and under- configured.
NEW QUESTION # 27
You are a knowledge worker evaluating which Claude feature matches each proposed use case.
Which two feature-to-use-case matches are appropriate? (Select two.)
Each correct answer presents a complete solution.
Answer: D,E
Explanation:
Option A appropriately uses Claude's long-context capabilities for a task involving many source documents.
A quarterly report may require Claude to compare evidence across financial results, operational updates, customer information, and prior reporting periods. Supplying the relevant sources in a well-organized context allows Claude to synthesize the material while following a consistent report structure. Source boundaries and attribution should remain clear so the final output can be validated.
Option E is also an appropriate match. A calculator or code-execution tool is suitable for complex, multi-step pricing calculations because it provides deterministic computation that can be inspected and tested. Claude can structure the calculation and interpret the result, while the tool performs the arithmetic more reliably.
Option B does not require long-context processing because a single short email can normally be handled directly in chat. Option C unnecessarily invokes web search for a stable, established formula that does not require current external information. Option D mismatches the tool to the task: simplifying product language is a writing and audience-adaptation task, not a numerical calculation.
Effective feature selection depends on the actual workload. Large source collections benefit from long-context synthesis, whereas precise arithmetic benefits from deterministic computational tools and explicit result validation.
NEW QUESTION # 28
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