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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Output Evaluation and Validation | 21% | - Evaluating output accuracy and completeness - Determining when human review or verification is required - Fact-checking and validation - Editing, adapting, and refining outputs - Identifying hallucinations, inconsistencies, and bias |
| Topic 2: Product and Model Selection | 12% | - Balancing quality, speed, and cost - Managing context limitations and memory - Selecting appropriate Claude product features - Selecting Claude models |
| Topic 3: Workflow Integration and Solution Design | 16% | - Analyzing requirements and use cases - Communicating Claude's value and limitations - Integrating Claude into existing workflows - Solution design and iteration - Research, planning, and process optimization |
| Topic 4: Prompting and Task Execution | 14% | - Adapting prompting strategies to task types - Creating effective prompts - Task decomposition - Iterating prompts to improve output |
| Topic 5: Configuration and Knowledge Management | 12% | - Managing uploaded knowledge and connectors - Maintaining configuration and knowledge sources - Configuring Claude Projects - Managing instructions and knowledge sources |
| Topic 6: Troubleshooting and Optimization | 10% | - Optimizing workflows for efficiency and effectiveness - Diagnosing underperforming prompts and outputs - Adjusting approaches based on feedback and results |
| Topic 7: Governance, Risk, and Responsible Use | 15% | - Identifying appropriate and inappropriate AI use cases - Ethical and responsible AI use - Data sensitivity, privacy, and regulatory considerations - Organizational AI governance and policies |
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NEW QUESTION # 16
A marketing associate is drafting Project custom instructions for a brand-voice writing workspace. The workspace will be used by several writers, and outputs need to be consistent across writers and chats.
Which approach is most likely to produce consistent outputs across many chats?
Answer: C
Explanation:
Project custom instructions should contain persistent behavioral requirements that apply to every conversation in the workspace. Option C is correct because it explicitly defines Claude's role, intended audience, brand attributes, tone boundaries, and terminology requirements. These elements collectively reduce ambiguity and help different writers obtain consistent results across separate chats.
Option A relies too heavily on a single example. Examples can demonstrate style, but they may not communicate every prohibited tone, terminology rule, or audience requirement. Option B delegates important persistent constraints to individual writers, creating predictable variation between chats. Option D places the glossary in Project knowledge but fails to make terminology compliance an explicit behavioral requirement.
Claude may reference knowledge files when relevant, but custom instructions should directly state that approved terminology must be followed.
The strongest configuration separates behavior from supporting material: custom instructions define what Claude must consistently do, while Project knowledge stores detailed glossaries, brand guides, approved examples, and other reference documents. This aligns with Claude Project guidance concerning reusable instructions, scoped knowledge, roles, workflows, and consistent output expectations.
NEW QUESTION # 17
A knowledge worker is applying the AI Fluency Framework Description competency while revising an underperforming prompt.
Which revision best reflects Description principles?
Answer: A
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 # 18
A project manager is defining how Claude can support requirements analysis for an upcoming engagement.
Their team will conduct stakeholder interviews and review existing process documentation as part of discovery.
Which activity fits this domain?
Answer: C
Explanation:
Option C is correct because requirements analysis is grounded in evidence gathered during discovery. Claude can help organize interview notes and process documentation, identify recurring themes, extract candidate requirements, flag conflicts, and produce a consistent structure. Requiring traceability to each source allows analysts to verify the output and return unclear or disputed requirements to the relevant stakeholder.
Option A asks Claude to invent a complete requirements set from insufficient context. Similar projects may provide useful hypotheses, but they cannot substitute for the organization's actual stakeholders, constraints, workflows, and objectives. Option B unnecessarily limits Claude's role: Claude can support synthesis and extraction as well as prioritization, provided qualified humans verify the results. Option D transfers the stakeholder-interview responsibility too broadly. Claude may help prepare questions, summarize authorized transcripts, or organize findings, but human analysts should manage stakeholder relationships, pursue contextual follow-ups, and interpret sensitive or ambiguous responses.
Anthropic recommends providing clear context and structured instructions, while its hallucination guidance advises grounding factual work in source text and auditable citations. A structured, source-traceable requirements list applies both principles and keeps humans responsible for validation and final decisions. See Anthropic's prompting best practices and source-grounding guidance .
NEW QUESTION # 19
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: C
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 # 20
You are a project lead reviewing a teammate's habit of using the same prompt template for every task regardless of type.
Which feedback is most warranted?
Answer: A
Explanation:
Different tasks require different prompting structures, evidence, constraints, and evaluation methods. A research request should define research questions, source requirements, currency expectations, and citation rules. An analytical task should specify the decision to support, relevant data, assumptions, and comparison criteria. Drafting work requires audience, tone, purpose, structure, and length. Brainstorming normally benefits from broader exploration, diversity requirements, and delayed evaluation.
A reusable template can provide a useful baseline, but it should not remain unchanged when task characteristics differ. Options B, C, and D incorrectly assume that uniformity guarantees effectiveness. In practice, excessive rigidity can omit critical instructions or impose an inappropriate structure. A compliance report and an early-stage ideation exercise should not be prompted identically.
Anthropic's prompting documentation covers multiple techniques-including clear instructions, examples, role prompting, structured formats, prompt chaining, and success criteria-because no single technique is optimal for every workload. Anthropic's legal-summarization guidance also demonstrates that prompt details can be adjusted for different levels of technicality, verbosity, and structure. The project lead should therefore standardize reusable components while adapting task-specific objectives, inputs, constraints, and output formats. Anthropic's prompt-engineering overview
NEW QUESTION # 21
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