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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prompting and Task Execution | 14% | - Apply task decomposition to structure complex requests - Adapt prompting strategies by task type - Create effective prompts for business and technical tasks - Iterate prompts to improve output quality |
| Topic 2: Troubleshooting and Optimization | 10% | - Adjust prompts and configuration to improve results - Identify causes of poor or unexpected outputs - Diagnose context and performance issues |
| Topic 3: Product and Model Selection | 12% | - Match model capabilities to task requirements - Understand model differences and use cases - Select appropriate Claude product features |
| 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: Governance, Risk, and Responsible Use | 15% | - Understand limitations and ethical boundaries - Manage data sensitivity and privacy risks - Apply responsible AI principles and policies |
| Topic 6: Configuration and Knowledge Management | 12% | - Configure Claude Projects with instructions - Manage knowledge sources and context - Maintain consistent system-level behavior |
| Topic 7: Output Evaluation and Validation | 21% | - Evaluate outputs for accuracy, completeness, and consistency - Detect hallucinations, biases, and inconsistencies - Determine when human review is required - Apply fact-checking and validation methods |
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NEW QUESTION # 107
You are a product manager asking Claude to produce an interactive prototype of a small landing-page mockup that the team will iterate on and share.
Which Claude feature is best suited to this output?
Answer: A
Explanation:
Option C is correct because an Artifact is designed for substantial, self-contained output that users need to inspect, edit, preview, and refine separately from the surrounding conversation. A landing-page prototype- particularly one containing HTML, CSS, JavaScript, or an interactive component-is more usable in a dedicated Artifact workspace than as code buried inside a chat response.
Artifacts support iterative development. The product manager can ask Claude to change the layout, copy, colors, component behavior, or responsive structure while maintaining a recognizable working version. The resulting prototype can also be reviewed or shared more effectively because it is presented as a distinct deliverable rather than as part of the conversation transcript.
Option A is a research workflow and would be appropriate for gathering sourced information about competitors, not for producing the prototype itself. Option B provides no dedicated editing or preview environment and makes repeated revisions harder to manage. Option D could preserve recurring instructions and reference materials, but a Project is a contextual workspace rather than the output format for the prototype.
A Project and an Artifact can be used together: the Project supplies persistent product requirements and design references, while the Artifact contains the actual prototype that the team iterates on.
NEW QUESTION # 108
You are an analyst reviewing a Claude response that addresses two of three required questions and skips the third.
Which prompt element most likely needs strengthening?
Answer: B
Explanation:
Under the objective Identify, diagnose, and resolve issues with underperforming prompts and/or poor outputs , diagnosing incomplete outputs requires mapping the specific failure mode directly to the corresponding prompt component.
When a model reliably answers some inquiries but completely omits another, the root cause is typically prompt ambiguity or buried instructions within dense prose. Strengthening the core task statement by explicitly enumerating the required deliverables (e.g., using numbered lists or tagged XML blocks like < question_1 > , < question_2 > , < question_3 > ) and mandating a complete response for each item (Option D) provides clear structural constraints that prevent omissions. Adding generic background context (Option A), changing persona framing (Option C), or relaxing output formatting constraints (Option B) fails to address the underlying instruction-following issue.
NEW QUESTION # 109
You are handling a document containing mixed-sensitivity content before using it with Claude.
Which data-handling step should be performed first?
Answer: B
Explanation:
Under the objective Apply data, privacy sensitivity, regulatory policies, and privacy considerations , responsible data management follows a strict, sequential security lifecycle when handling enterprise data for AI tasks.
Before any redaction, sanitization, or masking can occur, the user must first classify the document's data assets and systematically identify which elements constitute sensitive data (Option B)-such as Personally Identifiable Information (PII), Protected Health Information (PHI), or confidential corporate financial figures.
Without establishing data classification boundaries, redaction (Option A) becomes incomplete and error- prone. Only after identifying and classifying sensitive fields can one properly redact them (Option A), conduct a quality assurance/peer review (Option D), and ultimately submit the sanitized payload to Claude (Option C).
NEW QUESTION # 110
A manager is monitoring a Project's effectiveness over time. The Project has been in use for several months and supports a recurring workflow.
Which signal most directly suggests the configuration needs updating?
Answer: D
Explanation:
Answer C is correct. Increasing use of outdated terminology, sources, or guidance directly indicates that the Project's configuration or knowledge base no longer represents current business practice. Claude Projects use uploaded documents, contextual material, and Project instructions to guide responses across chats. When those inputs become obsolete, the resulting outputs can remain internally consistent while still being operationally inaccurate. The manager should review the Project instructions, replace outdated knowledge files, remove conflicting material, and test the revised configuration against representative workflow tasks.
Option A may reflect seasonal demand, reduced workload, or declining adoption; it does not directly demonstrate a configuration defect. Option B is also inconclusive because longer responses may result from changing task complexity or user preferences. Option D deserves investigation because users may be bypassing the Project due to usability or quality concerns, but it could equally result from habit, convenience, or insufficient training. By contrast, outdated references provide direct evidence that the Project's grounding information needs maintenance. Anthropic describes Projects as self-contained workspaces whose uploaded knowledge and instructions provide context and tailor Claude's responses. Those resources must therefore be reviewed and updated when organizational practices change. Anthropic: What are Projects?
NEW QUESTION # 111
You are a customer-success lead running an interactive workflow where each turn must respond quickly and the per-turn reasoning is light.
Which selection best aligns with the requirements?
Answer: D
Explanation:
Option A correctly matches the model tier to the workload. An interactive, high-volume workflow with light reasoning places greater importance on response speed, operational efficiency, and cost than on maximum reasoning depth. Haiku is positioned as the fast, lightweight Claude model for responsive tasks, making it the appropriate starting choice.
Option B uses a criterion unrelated to performance. Option C is incorrect because model tiers differ in capability, latency, and cost characteristics. Option D prioritizes advanced reasoning even though the scenario explicitly states that reasoning demands are light and rapid responses are required. Selecting a more capable model than the task needs can increase latency and expense without producing a meaningful business benefit.
Model selection should still be validated empirically. The team should define an acceptable quality threshold, test representative customer-success requests, measure response latency and task accuracy, and confirm that Haiku meets the required service level. If the real workload contains complex exceptions, the workflow could route only those cases to a more capable model. Anthropic's current learning materials characterize Haiku as its fastest option for lightweight work, while its prompt-engineering guidance identifies model selection as a direct lever for improving cost and latency. Anthropic's Claude learning resources
NEW QUESTION # 112
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