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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Workflow Integration and Solution Design | 16% | - Support solution design through iteration - Use Claude for research, planning, and process optimization - Analyze requirements and use cases - Integrate Claude into existing workflows and communicate its value and limitations |
| Topic 2: Product and Model Selection | 12% | - Select appropriate Claude product features - Manage context limitations and memory - Align model selection with task requirements - Differentiate between Claude model types |
| Topic 3: Output Evaluation and Validation | 21% | - Apply fact-checking and validation techniques - Evaluate Claude-generated outputs for accuracy and completeness - Identify hallucinations, inconsistencies, and biases in responses - Edit and adapt outputs for the intended audience - Determine when human review or additional verification is required - Organize and curate information and select appropriate output formats |
| Topic 4: Governance, Risk, and Responsible Use | 15% | - Identify appropriate and inappropriate use cases - Understand ethical implications of Claude use - Follow organizational AI policies and governance standards - Apply data sensitivity, regulatory, and privacy considerations |
| Topic 5: Prompting and Task Execution | 14% | - Adapt prompting strategy by task type - Iterate prompts to improve output quality - Create effective prompts for business and technical tasks - Apply task decomposition techniques to structure complex requests |
| Topic 6: Troubleshooting and Optimization | 10% | - Optimize workflows for efficiency and effectiveness - Identify and diagnose issues with underperforming prompts or poor outputs - Adjust approaches based on feedback and results |
| Topic 7: Configuration and Knowledge Management | 12% | - Maintain and update configurations - Create effective system-level instructions - Configure Claude Projects with instructions and knowledge sources - Manage uploaded knowledge and connectors |
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NEW QUESTION # 33
A communications manager is drafting a prompt for Claude to produce a quarterly newsletter for store managers in three regions. The agreed key messages, regional details, and a prior newsletter the team liked are all available.
Which prompt approach is most likely to produce a usable first draft?
Answer: C
Explanation:
Under the objective Create effective prompts for business and technical tasks , Anthropic's core prompt engineering principle emphasizes being explicit, direct, and providing complete structural constraints rather than relying on implicit document matching.
Option D establishes all essential prompt components directly within the prompt itself: explicitly defining the target audience (store managers), geographic scope (three regions), length constraints, tone guidelines, and the core messaging points, while treating the historical newsletter as a calibrated few-shot tone reference. This explicit framing eliminates ambiguity and prevents the model from copying obsolete structure or irrelevant sections from the historical document. In contrast, Option A relies excessively on broad pattern-matching against an attachment without providing explicit parameter boundaries in the prompt body. Option B lacks structural and tonal detail, while Option C delegates tone and length decisions entirely to the model.
NEW QUESTION # 34
A finance manager is about to discuss a confidential pre-announcement figure with Claude.
Which two settings best align with sound privacy practice for this conversation? (Select two.) Each correct answer presents a complete solution.
Answer: A,B
Explanation:
Under the objective Apply data, privacy sensitivity, regulatory policies, and privacy considerations , managing confidential or market-sensitive figures requires controlling memory persistence and data retention settings.
Pre-announcement financial figures represent material non-public information (MNPI) that must not persist beyond the immediate analytical session. Option E applies privacy controls by utilizing Incognito mode, which ensures the session does not contribute to long-term memory or persist in chat history. Option B achieves the same data protection control in standard chat by explicitly toggling off Memory contributions, ensuring the sensitive number is not saved into persistent memory where it could leak into future unrelated prompts. Conversely, proceeding with default settings (Option A), assuming brief discussions avoid retention (Option C), or enabling persistent memory retention for confidential figures (Option D) creates serious compliance and insider data exposure risks.
NEW QUESTION # 35
A sales manager is iterating on a Claude-generated solution prototype after a stakeholder review identified two specific concerns. The rest of the prototype was accepted as written.
Which iteration approach is most likely to produce a strong next version?
Answer: A
Explanation:
Option C applies controlled, evidence-based iteration. Because stakeholders accepted the remainder of the prototype, the next revision should concentrate specifically on the two identified concerns. Preserving approved sections reduces regression risk, maintains alignment with the accepted baseline, and makes the revised version easier for stakeholders to evaluate. Documenting the changes also provides traceability by showing exactly how each review comment was resolved.
Option A unnecessarily rebuilds the entire prototype and could introduce defects into sections that were already approved. Option B creates avoidable scope expansion by changing unrelated material without stakeholder justification. Even apparently minor stylistic revisions can alter meaning, behavior, or previously accepted design choices. Option D similarly introduces an unrequested third change, making it harder to determine whether the stakeholder-directed corrections produced the desired improvement.
Anthropic's Description-Discernment feedback loop recommends evaluating what worked and what did not, providing specific feedback, and refining the output based on that evaluation. Human judgment determines what should be kept, modified, or discarded. Targeted revision therefore produces a more controlled and reviewable next version than wholesale rewriting or adding unrelated improvements.
NEW QUESTION # 36
You are a content creator. A first response from Claude is accurate but uses inconsistent terminology that does not match your organization's glossary.
Which iterative change addresses the issue most directly?
Answer: C
Explanation:
Option C directly addresses both causes of the problem: Claude lacks the organization's authoritative terminology, and the prompt does not explicitly require adherence to it. Supplying the glossary gives Claude the necessary reference material, while instructing it to use only those terms converts the desired style into a clear and testable constraint.
Option A leaves terminology selection to Claude, so the resulting language may be internally consistent but still conflict with the organization's standards. Option B creates avoidable manual work and increases the possibility that some mismatched terms will be overlooked. Option D asks for consistency but fails to define which terminology is correct. Claude might consistently apply a term that is not approved by the organization.
Effective prompt iteration should diagnose the observed defect and introduce the missing information or instruction that directly resolves it. In this case, the issue is not factual accuracy, response length, or general writing quality. It is compliance with a controlled vocabulary. The revised prompt could also instruct Claude to flag concepts that have no approved glossary equivalent rather than inventing a replacement. For recurring work, the glossary and terminology rule could be placed in Project knowledge and Project instructions so that the constraint is applied consistently across related conversations.
NEW QUESTION # 37
You are a knowledge worker summarizing common prompt failure patterns for the team.
Which pattern most often produces vague or off-target output?
Answer: B
Explanation:
Option A describes an under-specified prompt. Naming only a topic does not tell Claude what action to perform, who will use the result, which information should receive priority, or how the response must be organized. Claude must then infer these requirements, increasing the likelihood of a generic, mis-scoped, or incorrectly formatted response.
An effective business prompt normally identifies the task, supplies relevant context, defines the intended audience, states the desired output structure, and includes material constraints such as tone, length, scope, or exclusions. A representative example can further clarify the expected standard. Consequently, Options B, C, and D describe techniques that generally reduce ambiguity rather than cause it.
Anthropic's prompting guidance recommends clear, detailed instructions and relevant context, while its prompt-engineering framework assumes that users first define success criteria and a testable objective. The prompt should make the expected behavior observable: "summarize this policy for store managers in a five- bullet briefing" is materially stronger than "employee policy." When an output is vague, the correct diagnosis is usually not insufficient model capability but insufficiently described intent, audience, or format. Claude usage and prompting guidance
NEW QUESTION # 38
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