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| Section | Weight | Objectives |
|---|---|---|
| Prompting and Task Execution | 14% | - Adapt prompting strategy by task type - Create effective prompts for business and technical tasks - Iterate prompts to improve output quality - Apply task decomposition techniques to structure complex requests |
| Product and Model Selection | 12% | - Select appropriate Claude product features - Differentiate between Claude model types - Manage context limitations and memory - Align model selection with task requirements |
| Governance, Risk, and Responsible Use | 15% | - Understand ethical implications of Claude use - Identify appropriate and inappropriate use cases - Follow organizational AI policies and governance standards - Apply data sensitivity, regulatory, and privacy considerations |
| Configuration and Knowledge Management | 12% | - Configure Claude Projects with instructions and knowledge sources - Manage uploaded knowledge and connectors - Maintain and update configurations - Create effective system-level instructions |
| Troubleshooting and Optimization | 10% | - Adjust approaches based on feedback and results - Identify and diagnose issues with underperforming prompts or poor outputs - Optimize workflows for efficiency and effectiveness |
| Workflow Integration and Solution Design | 16% | - Use Claude for research, planning, and process optimization - Analyze requirements and use cases - Support solution design through iteration - Integrate Claude into existing workflows and communicate its value and limitations |
| Output Evaluation and Validation | 21% | - Organize and curate information and select appropriate output formats - Edit and adapt outputs for the intended audience - Evaluate Claude-generated outputs for accuracy and completeness - Apply fact-checking and validation techniques - Identify hallucinations, inconsistencies, and biases in responses - Determine when human review or additional verification is required |
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NEW QUESTION # 23
You are evaluating proposed workflow changes against whether they meaningfully improve the workflow.
Which two proposed changes meaningfully improve a recurring Claude workflow? (Select two.) Each correct answer presents a complete solution.
Answer: B,D
Explanation:
Under the objective Optimize workflows for efficiency and effectiveness , meaningful operational improvements must deliver measurable gains in throughput, token efficiency, or output reliability.
Option C provides major efficiency gains by moving recurring reference documentation into a persistent Claude Project knowledge base, eliminating redundant token overhead and manual copy-pasting across dozens of daily chats. Option E provides vital effectiveness and risk mitigation by establishing a standardized human-in-the-loop quality gate, preventing defective or hallucinated outputs from propagating into downstream operational pipelines. In contrast, renaming workspaces (Option A), re-labeling steps for cosmetic readability (Option B), or shuffling documentation headings (Option D) represent superficial administrative edits that do not improve execution speed, cost, or output quality.
NEW QUESTION # 24
You have iterated a Claude prompt eight times, and the output quality has plateaued for the last four attempts.
Which conclusion is most appropriate?
Answer: B
Explanation:
Under the objective Adjust approach based on feedback and results , recognizing the law of diminishing returns in prompt engineering is essential for operational efficiency.
When a prompt has undergone multiple revision cycles (e.g., eight iterations) and the output quality plateaus with no observable improvement over four consecutive attempts, further micro-tweaks to the prompt text are unlikely to succeed. Option C provides the appropriate path forward: recognizing that the prompting approach has plateaued and pivoting either to direct human editing/review (human-in-the-loop completion) or fundamentally redesigning the workflow strategy (such as decomposing the task into smaller chained sub- prompts or switching model tiers). In contrast, accepting flawed output uncritically (Option A) compromises standards, abandoning the initiative silently (Option B) violates project accountability, and iterating indefinitely (Option D) wastes time and token budget.
NEW QUESTION # 25
You are an operations manager preparing a quick reference card for a team.
Which description correctly characterizes the three Claude model tiers in general terms?
Answer: C
Explanation:
Under the objective Differentiate between Claude model types (e.g., Haiku, Sonnet, Opus) (Domain 3:
Product and Model Selection), Anthropic structures its model family across three clear tiers of intelligence, latency, and cost:
* Claude Haiku : The fastest, most cost-efficient, and lightweight model designed for high-volume, low- latency tasks and simple classification.
* Claude Sonnet : The balanced, versatile enterprise workhorse combining high intelligence and throughput for everyday knowledge-work tasks.
* Claude Opus : The frontier model offering deep reasoning and analytical capacity for complex, multi- step problem solving at higher latency and operational cost.
Option C perfectly summarizes these structural trade-offs. Options A, B, and D misrepresent the capability hierarchy, speed profiles, and architectural tiering of the Claude family.
NEW QUESTION # 26
You are a procurement associate decomposing a vendor-evaluation task.
Which dependency ordering reflects sound sequencing?
Answer: B
Explanation:
Option A is correct because vendor evaluation must begin with an agreed decision framework. The organization should first define relevant criteria, measurement methods, mandatory requirements, scoring weights, acceptable evidence, and disqualification conditions. Typical criteria might cover capability, security, compliance, implementation effort, support, total cost, and contractual risk.
Vendor information can then be gathered consistently against the same framework. Claude may help extract evidence from proposals, populate a comparison structure, identify missing information, and calculate scores when the rules are explicitly defined. After the evidence has been validated, the vendors can be scored and ranked. This sequence supports fairness, traceability, and repeatability.
Options B, C, and D reverse or omit essential dependencies. Asking Claude for a recommendation without inputs invites unsupported assumptions. Scoring before defining criteria permits the desired outcome to influence the evaluation framework. Ranking before collecting evidence has no defensible analytical basis.
Anthropic recommends defining specific, measurable, relevant success criteria before building evaluations.
The same principle applies to vendor selection: criteria must precede measurement and judgment.
Therefore, the sound dependency chain is criteria definition, evidence collection, validation, scoring, and ranking. See Anthropic's guidance on defining success criteria and evaluations .
NEW QUESTION # 27
You have iterated a Claude prompt eight times, and the output quality has plateaued for the last four attempts.
Which conclusion is most appropriate?
Answer: B
NEW QUESTION # 28
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