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| Section | Weight | Objectives |
|---|---|---|
| Product and Model Selection | 12% | - Selecting Claude models - Selecting appropriate Claude product features - Managing context limitations and memory - Balancing quality, speed, and cost |
| Governance, Risk, and Responsible Use | 15% | - Identifying appropriate and inappropriate AI use cases - Data sensitivity, privacy, and regulatory considerations - Ethical and responsible AI use - Organizational AI governance and policies |
| Output Evaluation and Validation | 21% | - Identifying hallucinations, inconsistencies, and bias - Evaluating output accuracy and completeness - Fact-checking and validation - Editing, adapting, and refining outputs - Determining when human review or verification is required |
| Prompting and Task Execution | 14% | - Adapting prompting strategies to task types - Iterating prompts to improve output - Creating effective prompts - Task decomposition |
| Workflow Integration and Solution Design | 16% | - Integrating Claude into existing workflows - Solution design and iteration - Research, planning, and process optimization - Analyzing requirements and use cases - Communicating Claude's value and limitations |
| Configuration and Knowledge Management | 12% | - Managing instructions and knowledge sources - Managing uploaded knowledge and connectors - Configuring Claude Projects - Maintaining configuration and knowledge sources |
| Troubleshooting and Optimization | 10% | - Adjusting approaches based on feedback and results - Optimizing workflows for efficiency and effectiveness - Diagnosing underperforming prompts and outputs |
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NEW QUESTION # 149
As part of a workflow redesign, a process analyst is applying the AI Fluency Framework Delegation competency.
Which two criteria most directly inform Delegation decisions? (Select two.)
Answer: A,E
Explanation:
Options B and E are correct because Delegation requires evaluating both the capabilities needed for a task and the risk created by assigning it to AI. Anthropic defines Delegation as thoughtfully deciding which work should be completed by a human, performed collaboratively, or handled independently by AI. Tasks requiring distinctly human empathy, creativity, contextual judgment, accountability, or value-based decisions are less suitable for complete delegation. Claude may assist, but a human should retain control of the consequential decision.
Reversibility and error consequences are also critical. A low-impact, easily checked draft can generally receive more AI autonomy than an irreversible action or a decision that could materially affect people.
Anthropic's research on workplace AI use similarly reports that employees tend to delegate tasks that are low- stakes and readily verifiable while applying active supervision to high-stakes work.
Workflow age, diagram complexity, and employee seniority are indirect characteristics; they do not establish whether Claude has the required capabilities or whether an error can be safely corrected. An old workflow can still contain unsuitable tasks, and a junior employee may perform highly sensitive work. Thus, B and E provide the most relevant task-level and risk-level criteria. See Anthropic's Delegation lesson and research on workplace AI delegation .
NEW QUESTION # 150
An operations assistant is redesigning a recurring data-processing workflow step to use Code Execution.
Which two design choices best support reliable integration? (Select two.)
Answer: A,B
Explanation:
Options A and E are correct because reliable automation requires controlled inputs and validated outputs.
Standardizing the expected input format reduces parsing failures, inconsistent field mappings, and uncontrolled variation between weekly runs. The integration should define required columns, data types, date formats, permitted null values, file naming conventions, and error-handling behaviour. This makes results comparable and supports repeatable testing.
Human verification remains necessary because successful code execution proves only that the program completed without a runtime error. It does not prove that the source data was correct, the implemented calculation matched the business requirement, or the result is operationally reasonable. A sanity check against an expected range, reconciled total, sample calculation, or known baseline helps detect silent logical and data- quality errors before downstream use.
Option B introduces avoidable variability and should instead be handled through standardized preprocessing or explicit adapters. Option C creates an undocumented interface that downstream consumers cannot reliably interpret. Option D confuses sandbox isolation and successful execution with result validation. Anthropic confirms that Code Execution can process files, perform calculations, and generate analytical outputs in a sandbox, but its outputs must still be evaluated against task-specific success criteria. See Anthropic's Code Execution documentation and evaluation guidance .
NEW QUESTION # 151
You are prioritizing optimization actions across a recurring Claude workflow.
Which optimization action typically has the highest impact in a recurring knowledge workflow?
Answer: A
Explanation:
Option A generally creates the greatest recurring benefit because it converts an informal, repeatedly reconstructed process into a reusable Claude workspace. A properly configured Project can preserve stable instructions, authoritative reference materials, terminology rules, audience requirements, output expectations, and workflow constraints across related conversations. This reduces repeated context-setting and helps different team members obtain more consistent results.
Option C may improve the next execution, but a prompt stored informally can still be copied incorrectly, separated from its references, or used without the latest organizational requirements. Codifying the workflow within a Project makes the improved prompt and its supporting context reusable. Option B can make deliverables easier to read, but it primarily affects presentation rather than the reliability and efficiency of the complete workflow. Option D improves file organization after the output is generated but does not directly strengthen Claude's input, reasoning context, or output consistency.
The Project should still be tested with representative requests and maintained over time. Teams must update stale references, refine instructions when recurring defects appear, and document any required human-review steps. Nevertheless, when a knowledge workflow is repeated frequently, centralizing its persistent context and instructions typically produces a broader improvement than editing a single prompt, template, or storage location.
NEW QUESTION # 152
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 # 153
You are validating evaluation criteria proposed for a Claude-generated business brief.
Which three criteria are valid for evaluating a Claude-generated brief? (Select three.) Each correct answer presents part of the solution.
Answer: A,B,E
Explanation:
Options A, B, and C are correct. The source document incorrectly instructed the reader to select two and omitted Option B, even though Anthropic explicitly recognizes tone and style as valid evaluation dimensions.
The question has therefore been corrected to "Select three."
Factual accuracy measures whether claims faithfully reflect the supplied sources. Style consistency evaluates whether the brief follows the organization's established voice, terminology, and audience expectations.
Format and length compliance determine whether Claude followed explicit deliverable constraints. Together, these criteria cover factual fidelity, audience suitability, and instruction adherence.
Option D is not a sound criterion because an external industry word-count benchmark may have no relationship to the actual business need. The relevant measure is compliance with the requested length and sufficient coverage of the required material. Option E is also invalid as written: an executive summary is required only if the task specification, template, or audience needs call for one. Automatically demanding it would evaluate an unstated requirement.
Anthropic's evaluation documentation identifies task fidelity, relevance, tone and style, context utilization, and other task-specific success criteria as valid dimensions. It also stresses that criteria should be specific, measurable, achievable, and relevant. See Anthropic's official evaluation guidance .
NEW QUESTION # 154
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