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| Section | Weight | Objectives |
|---|---|---|
| Workflow Integration and Solution Design | 16% | - Use Claude for research, planning, and process optimization - Support solution design through iteration - Integrate Claude into existing workflows and communicate its value and limitations - Analyze requirements and use cases |
| Configuration and Knowledge Management | 12% | - Create effective system-level instructions - Configure Claude Projects with instructions and knowledge sources - Maintain and update configurations - Manage uploaded knowledge and connectors |
| Prompting and Task Execution | 14% | - Create effective prompts for business and technical tasks - Apply task decomposition techniques to structure complex requests - Iterate prompts to improve output quality - Adapt prompting strategy by task type |
| Product and Model Selection | 12% | - Align model selection with task requirements - Differentiate between Claude model types - Select appropriate Claude product features - Manage context limitations and memory |
| Governance, Risk, and Responsible Use | 15% | - Apply data sensitivity, regulatory, and privacy considerations - Identify appropriate and inappropriate use cases - Follow organizational AI policies and governance standards - Understand ethical implications of Claude use |
| Output Evaluation and Validation | 21% | - Organize and curate information and select appropriate output formats - Identify hallucinations, inconsistencies, and biases in responses - Evaluate Claude-generated outputs for accuracy and completeness - Edit and adapt outputs for the intended audience - Determine when human review or additional verification is required - Apply fact-checking and validation techniques |
| Troubleshooting and Optimization | 10% | - Identify and diagnose issues with underperforming prompts or poor outputs - Optimize workflows for efficiency and effectiveness - Adjust approaches based on feedback and results |
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NEW QUESTION # 125
A business analyst is converting a sticky-note request from a stakeholder into a structured prompt for Claude.
Which is the correct order of conversion steps?
(1) Confirm the audience and the decision the response must support.
(2) Submit the structured prompt to Claude.
(3) Identify the underlying task hidden in the sticky-note language.
(4) Specify the desired length, tone, and output format.
(5) Add the supporting facts and constraints relevant to the task.
Answer: B
Explanation:
Answer C gives the proper conversion sequence. The analyst first determines the real task hidden behind the informal sticky-note wording (3); without that step, the prompt may solve the wrong problem. Next, the analyst confirms who will consume the result and which decision it must support (1). Audience and decision purpose determine what evidence is relevant, so the supporting facts, boundaries, and constraints are added afterward (5). Once the substantive requirements are stable, the analyst specifies presentation requirements such as length, tone, and output format (4). The completed prompt can then be submitted to Claude (2). This yields 3, 1, 5, 4, 2. Option A starts with the audience before clarifying the underlying task. Option D supplies facts before establishing the decision context, which can result in irrelevant or insufficient context. Option B begins by submitting a prompt that has not yet been structured. Anthropic's official prompting guidance says Claude performs best with clear, explicit instructions, relevant context, precise output constraints, and sequentially stated steps when order or completeness matters. These principles align directly with the AI Fluency Description competency: clearly describe the intended product, process, and interaction before expecting a reliable result. Anthropic prompting best practices
NEW QUESTION # 126
A knowledge worker is explaining how to use feedback to improve Claude-supported work over time.
Which description is most accurate?
Answer: B
Explanation:
Under the objective Adjust approach based on feedback and results , iterative refinement requires tight, closed feedback loops characterized by concrete observation, targeted modification, and empirical evaluation.
Option A details the gold-standard iteration cycle: capturing specific, granular defects immediately following an execution run (e.g., tone misalignment, omitted edge cases, formatting errors), translating those observations into targeted, discrete adjustments in prompt instructions or workflow logic, and validating whether subsequent outputs resolve the issue without regressions. In contrast, deferring feedback collection across multiple unmonitored cycles (Option B) delays error detection. Relying solely on high-level aggregate numerical ratings (Option C) lacks the actionable diagnostic detail needed to locate root causes. Applying sweeping, unfocused prompt overhauls (Option D) obscures cause-and-effect relationships and frequently introduces new failure modes.
NEW QUESTION # 127
An HR associate is preparing to use Claude on a sensitive personnel matter. The organization's AI policy explicitly states that information related to ongoing investigations must not be entered into AI tools.
Which response best aligns with the policy?
Answer: B
Explanation:
Under the objective Apply data, privacy sensitivity, regulatory policies, and privacy considerations , compliance with explicit organizational AI governance and data boundary mandates is mandatory.
When corporate policy strictly prohibits entering information concerning active personnel investigations into AI tools, employees must fully adhere to that boundary without attempting informal workarounds. Option B correctly enforces compliance: immediately refraining from submitting any investigation-related text to Claude and escalating to HR leadership to determine authorized, conventional processing channels.
Attempting to bypass the rule via Incognito mode (Option C) or informal paraphrasing/anonymization (Option D) violates the explicit governance mandate and risks data spillage in legally sensitive matters.
Assuming the data can simply be entered once closed (Option A) ignores enduring confidentiality requirements.
NEW QUESTION # 128
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: A
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 # 129
Before uploading a customer file for a Code Execution analysis, a customer-success associate at Noventra, Ltd. is reviewing the planned task.
Which two practices best align with sound data handling? (Select two.)
Answer: A,E
Explanation:
Options B and E apply organizational governance and data-minimization requirements before the file enters Claude's execution environment. The associate must first establish whether Code Execution is an approved processing method for the file's classification. If the information exceeds the approved sensitivity level, the user must escalate to privacy, security, legal, or another designated authority rather than proceeding independently.
The file must also be inspected for customer identifiers, confidential fields, regulated information, credentials, or data unrelated to the calculation. Unnecessary fields should be removed, redacted, or anonymized. A sandbox limits interaction with the surrounding system, but it does not change the sensitivity of uploaded data, provide authorization, or override the organization's handling rules. Therefore, Options C and D incorrectly treat technical isolation as a governance exemption. Option A allows urgency to displace mandatory review.
Anthropic explains that Code Execution runs in an isolated container, while also warning that file-processing configurations and network access create security considerations. Its privacy guidance recommends careful treatment of highly sensitive personal and confidential information. The correct control is to minimize and authorize the data before uploading it, not rely solely on the sandbox afterward. Anthropic's Code Execution security guidance
NEW QUESTION # 130
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