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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Workflow Integration and Solution Design | 16% | - Support solution design through iteration - Integrate Claude into existing workflows and communicate its value and limitations - Use Claude for research, planning, and process optimization - Analyze requirements and use cases |
| Topic 2: Governance, Risk, and Responsible Use | 15% | - Follow organizational AI policies and governance standards - Understand ethical implications of Claude use - Identify appropriate and inappropriate use cases - Apply data sensitivity, regulatory, and privacy considerations |
| Topic 3: Product and Model Selection | 12% | - Differentiate between Claude model types - Align model selection with task requirements - Manage context limitations and memory - Select appropriate Claude product features |
| Topic 4: Configuration and Knowledge Management | 12% | - Maintain and update configurations - Configure Claude Projects with instructions and knowledge sources - Manage uploaded knowledge and connectors - Create effective system-level instructions |
| Topic 5: Output Evaluation and Validation | 21% | - Organize and curate information and select appropriate output formats - Apply fact-checking and validation techniques - Determine when human review or additional verification is required - Evaluate Claude-generated outputs for accuracy and completeness - Identify hallucinations, inconsistencies, and biases in responses - Edit and adapt outputs for the intended audience |
| Topic 6: Prompting and Task Execution | 14% | - Create effective prompts for business and technical tasks - Adapt prompting strategy by task type - Apply task decomposition techniques to structure complex requests - Iterate prompts to improve output quality |
| Topic 7: Troubleshooting and Optimization | 10% | - Optimize workflows for efficiency and effectiveness - Adjust approaches based on feedback and results - Identify and diagnose issues with underperforming prompts or poor outputs |
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NEW QUESTION # 93
A customer-success associate is drafting a prompt that asks Claude to summarize a customer issue from the case file. The case file includes the customer ' s full government identifier, home address, name, account number, and the description of the issue. The summary the associate needs is about the issue.
Which approach is most appropriate?
Answer: D
Explanation:
Under the objective Apply data, privacy sensitivity, regulatory policies, and privacy considerations (Domain
6: Governance, Risk, and Responsible Use), data minimization is a primary privacy requirement.
When processing enterprise documents with AI tools, users must never submit highly sensitive Personally Identifiable Information (PII)-such as national government identifiers (SSNs/National Insurance numbers) or private home addresses-unless strictly required for the analytical task. Because the associate only needs a summary of the core customer problem, redacting or removing those non-essential high-sensitivity fields prior to input ingestion (Option C) enforces sound privacy hygiene. Relying on in-prompt instructions to " ignore " ingested PII (Option A) still exposes raw sensitive tokens to the model context. Swapping identifiers for other sensitive account data (Option B) fails data protection standards.
NEW QUESTION # 94
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: B
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 # 95
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 # 96
A knowledge worker is applying the AI Fluency Framework Description competency while revising an underperforming prompt.
Which revision best reflects Description principles?
Answer: C
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 # 97
You are running an optimization pass on a recurring workflow.
Which is the correct order of optimization steps?
(1) Apply targeted optimization to the bottleneck step.
(2) Roll out the optimized workflow to the broader team and document the change.
(3) Identify the bottleneck step using measured time per step and queue length.
(4) Map the current workflow steps, owners, and decision points.
(5) Pilot the change with a small group and measure the effect against the prior baseline.
Answer: D
Explanation:
The correct sequence is 4,3,1,5,2. Optimization must begin by mapping the current workflow, including its steps, owners, inputs, handoffs, and decision points. Without an accurate current-state map, the team cannot reliably associate delays or defects with a particular stage. It should then use measured evidence-such as processing time, waiting time, queue length, rework, or error frequency-to identify the actual bottleneck.
After locating the constraint, the team can apply a targeted improvement to that step. Changing the workflow before identifying the bottleneck, as in Option C, risks optimizing a noncritical activity while leaving the primary delay untouched. The change should next be piloted with a limited group and compared against the previous baseline. This determines whether the intervention improves throughput or quality without creating downstream problems. Only after a successful pilot should the process be rolled out broadly and formally documented.
This sequence is consistent with Anthropic's evaluation approach: define measurable criteria, test changes against representative conditions, and validate performance before production use. Option D identifies the bottleneck before establishing the workflow map needed to interpret the measurements. Anthropic's evaluation guidance
NEW QUESTION # 98
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