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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Output Evaluation and Validation | 21% | - Determine when human review is required - Apply fact-checking and validation methods - Evaluate outputs for accuracy, completeness, and consistency - Detect hallucinations, biases, and inconsistencies |
| Topic 2: Configuration and Knowledge Management | 12% | - Configure Claude Projects with instructions - Maintain consistent system-level behavior - Manage knowledge sources and context |
| Topic 3: Troubleshooting and Optimization | 10% | - Adjust prompts and configuration to improve results - Identify causes of poor or unexpected outputs - Diagnose context and performance issues |
| Topic 4: Workflow Integration and Solution Design | 16% | - Design AI-assisted processes and solutions - Plan end-to-end Claude-augmented workflows - Integrate Claude into existing business workflows |
| Topic 5: Prompting and Task Execution | 14% | - Iterate prompts to improve output quality - Adapt prompting strategies by task type - Apply task decomposition to structure complex requests - Create effective prompts for business and technical tasks |
| Topic 6: Product and Model Selection | 12% | - Understand model differences and use cases - Select appropriate Claude product features - Match model capabilities to task requirements |
| Topic 7: Governance, Risk, and Responsible Use | 15% | - Understand limitations and ethical boundaries - Apply responsible AI principles and policies - Manage data sensitivity and privacy risks |
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NEW QUESTION # 35
You are an operations lead mapping production tasks to Claude model strengths to set realistic expectations.
Which two production tasks fit Claude's strengths most clearly? (Select two.) Each correct answer presents a complete solution.
Answer: D,E
Explanation:
Under the objective Differentiate between Claude model types (e.g., Haiku, Sonnet, Opus) and foundational AI capabilities, generative models are specifically optimized for natural language understanding, cross-document synthesis, and nuanced stylistic drafting.
Drafting audience-tailored, empathetic customer communications for human review (Option C) and synthesizing large volumes of complex source text into concise executive summaries (Option E) leverage Claude's extensive context window and linguistic fluency. Conversely, tasks requiring millisecond real-time event-driven streaming detection (Option A) or high-frequency deterministic quantitative financial settlement calculations on live feeds (Option D) are poorly suited for general LLMs and require specialized, deterministic streaming engines. Additionally, delegating final binding legal rulings entirely to an AI (Option B) represents an inappropriate governance risk.
NEW QUESTION # 36
An support representative is configuring a Project for drafting customer-facing apology emails after service outages. The current custom instructions tell Claude to " be empathetic and casual, keep it short, and offer a goodwill credit. " The customer-service team has flagged that recent drafts have been too brief, have offered goodwill credits in cases where policy does not allow them, and have used contractions that the brand voice guide prohibits.
Which adjustment best aligns the configuration to the use case?
Answer: D
Explanation:
Under the Claude objective Configure Claude Projects with instructions and knowledge sources, effective project configuration requires replacing vague, conflicting directives with explicit operational boundaries and grounded criteria. In this scenario, the root causes of underperformance are conflicting requirements: the prompt requests a " casual " tone while brand guidelines prohibit contractions, asks Claude to " keep it short " leading to overly brief outputs, and unconditionally directs it to " offer a goodwill credit " without verifying eligibility criteria.
Option C properly resolves all three deficiencies directly within the project instructions. First, it explicitly operationalizes the tone attributes (empathetic, formal, avoiding contractions) rather than relying on ambiguous descriptors. Second, establishing concrete length constraints (such as minimum paragraph or sentence counts) prevents the model from generating under-scoped drafts. Third, it conditions the business logic-instructing Claude to evaluate goodwill credit awards against the attached policy document in the Project knowledge base. In contrast, relying solely on uploaded knowledge files without aligning custom instructions (Options B and D) leads to prompt collisions, while Option A removes necessary policy guidance altogether.
NEW QUESTION # 37
You are an operations lead sorting Claude-driven research tasks by which deliver the most value.
Which two Claude-driven research tasks deliver the highest value in a typical analysis workflow? (Select two.) Each correct answer presents a complete solution.
Answer: A,B
Explanation:
Options A and D provide the highest analytical leverage. Synthesizing a large collection of interview transcripts requires reading extensive qualitative material, finding repeated themes, comparing perspectives, and organizing evidence into a usable structure. Claude can significantly reduce the time required for this work, provided the analyst validates the themes and retains traceability to the underlying interviews.
Drafting a comparative summary from public materials is similarly valuable because Claude can organize information across multiple sources, identify meaningful differences, and create a consistent comparison framework. The reviewer must still verify factual claims, source currency, and whether important counterevidence was omitted.
Option B is primarily visual formatting work and does not capitalize on Claude's strongest language-analysis capabilities. Option C may be useful, but basic transcription is normally a narrower processing task than cross- source synthesis or comparative analysis. Option E is inappropriate because fabricated "representative" quotations could be mistaken for actual customer evidence. Claude should summarize themes or label synthetic examples explicitly, never manufacture quotations and present them as research findings.
Claude creates the greatest research value when it accelerates source-grounded synthesis while a human remains responsible for validation, interpretation, and downstream decisions.
NEW QUESTION # 38
You are a marketing manager using Claude to ideate concepts for a campaign and must complete the framing steps before generating concepts.
Which two framing steps must be completed BEFORE asking Claude to generate concepts? (Select two.) Each correct answer presents part of the solution.
Answer: A,B
Explanation:
Effective ideation requires a clear creative frame. Option A defines what the campaign is intended to achieve and how success will be assessed. Option D defines the intended audience and brand voice, ensuring that generated concepts are relevant to the people being addressed and consistent with the organization's identity.
Options B and C occur after concepts have been generated. A finalist cannot be selected or developed until candidate concepts exist. Option E concerns execution planning and should follow concept selection, validation, and approval. Scheduling does not provide the creative direction Claude needs during initial ideation.
A strong ideation prompt might specify the campaign objective, audience characteristics, brand attributes, channel, constraints, prohibited themes, desired number of concepts, and the dimensions along which the ideas should differ. Claude can then explore broadly within meaningful boundaries. Success metrics also create criteria for evaluating ideas after generation, preventing selection from being driven solely by subjective preference.
Anthropic's prompting guidance emphasizes providing clear context, objectives, audience information, and output expectations. For brainstorming, the framing should constrain relevance without prescribing the final answer so tightly that concept diversity is eliminated. Anthropic's prompting best practices
NEW QUESTION # 39
You are a knowledge worker reviewing a Claude-generated brief that asserts a "well-known industry standard" without naming any source.
How should this assertion be handled?
Answer: B
Explanation:
The phrase "well-known industry standard" is not evidence. Without the name of the standard, its issuing body, version, publication date, or an authoritative citation, the statement cannot be independently verified.
Option D correctly treats the assertion as unsupported and requires either authoritative substantiation or removal.
Claude can produce fluent, confident language that appears credible even when the underlying claim is incomplete, inaccurate, or fabricated. Adding stronger language, as proposed in Option A, would amplify the unsupported claim rather than correct it. Options B and C confuse plausibility and confidence with verification. A claim does not become reliable merely because it sounds familiar or uses reassuring terminology.
The reviewer should identify the purported standard, locate the original issuing organization or official publication, confirm that the standard applies to the subject and jurisdiction, and cite the relevant section. If those checks cannot be completed, the claim should be deleted or rewritten to disclose uncertainty. Anthropic recommends grounding factual statements in direct source material, using citations to make claims auditable, and retracting claims for which supporting evidence cannot be found. This approach directly addresses hallucination risk while preserving the brief's credibility. Anthropic's hallucination-reduction guidance
NEW QUESTION # 40
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