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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Output Evaluation and Validation | 21% | - Evaluate outputs for accuracy, completeness, and consistency - Apply fact-checking and validation methods - Determine when human review is required - Detect hallucinations, biases, and inconsistencies |
| Topic 2: Governance, Risk, and Responsible Use | 15% | - Manage data sensitivity and privacy risks - Apply responsible AI principles and policies - Understand limitations and ethical boundaries |
| Topic 3: 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 4: Prompting and Task Execution | 14% | - Adapt prompting strategies by task type - Create effective prompts for business and technical tasks - Iterate prompts to improve output quality - Apply task decomposition to structure complex requests |
| Topic 5: Product and Model Selection | 12% | - Select appropriate Claude product features - Understand model differences and use cases - Match model capabilities to task requirements |
| Topic 6: Configuration and Knowledge Management | 12% | - Maintain consistent system-level behavior - Configure Claude Projects with instructions - Manage knowledge sources and context |
| Topic 7: Troubleshooting and Optimization | 10% | - Identify causes of poor or unexpected outputs - Diagnose context and performance issues - Adjust prompts and configuration to improve results |
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NEW QUESTION # 37
You are a Claude associate troubleshooting a recurring poor output.
Which is the correct order of diagnostic steps?
(1) Form a hypothesis about which prompt element most likely caused the deficiency.
(2) Apply a single targeted change and observe the effect on the output.
(3) Read the output end to end and identify the specific deficiency.
(4) Compare the deficient output to the prompt to spot mismatches between input and output.
(5) Document the root cause and the resolution for future reference.
Answer: B
Explanation:
Under the objective Identify, diagnose, and resolve issues with underperforming prompts and/or poor outputs (Domain 7: Troubleshooting and Optimization), troubleshooting follows a structured diagnostic protocol.
The troubleshooting sequence begins with symptom identification: reading the output end-to-end to categorize the exact flaw (e.g., factual error, structural omission, tone mismatch) (Step 3). Second, the practitioner performs an input-output diff: comparing the deficient output against the prompt instructions to spot instruction omissions or ambiguities (Step 4). Third, the practitioner forms a testable hypothesis regarding which prompt element caused the failure (Step 1). Fourth, they execute a controlled experiment by applying a single targeted prompt adjustment and observing the revised output (Step 2). Finally, they document the verified root cause and solution (Step 5). This establishes the order 3, 4, 1, 2, 5 .
NEW QUESTION # 38
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: C
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 # 39
You are an operations team member preparing inputs to summarize customer feedback. The feedback file mixes public quotations with personal contact details.
Which preparation approach is most appropriate?
Answer: D
Explanation:
Option D follows data-minimization and purpose-limitation principles. The task requires analysis of customer feedback, not access to customer contact information. The appropriate preparation process is therefore to retain the feedback statements needed for the analysis while removing names, email addresses, telephone numbers, account identifiers, and other unnecessary personal information.
Option A removes the useful content while retaining the sensitive data, directly reversing the correct handling approach. Option B exposes unnecessary personal information merely to provide more context. Option C discards the genuine feedback and invites Claude to fabricate replacement content, producing an unreliable summary. Redaction or anonymization preserves the analytical value of the input while reducing privacy exposure and limiting the consequences of unauthorized disclosure.
Anthropic advises users to be thoughtful about sharing highly sensitive personal or confidential information.
Its implementation guidance also recommends removing personally identifiable information unless it is explicitly required and authorized. Redaction does not override organizational policy: the user must still confirm that the approved Claude environment, access controls, contractual terms, retention settings, and intended purpose permit the remaining data to be processed. Anthropic's sensitive-data guidance
NEW QUESTION # 40
You are a knowledge manager structuring source material in the context window for a long Claude evaluation task.
Which two practices produce a more effective use of the context window? (Select two.) Each correct answer presents a complete solution.
Answer: C,D
Explanation:
Under the objective Organize and curate information for optimal outputs and select appropriate output formats , structuring reference documents effectively within the context window ensures high-fidelity retrieval and accurate source attribution.
Option B highlights the standard prompt engineering practice of using distinct structural delimiters (such as XML tags like < doc_1 > , < policy > , or Markdown code fences). Delimiters allow Claude to distinguish cleanly between different source boundaries, instructions, and inputs, minimizing attribution errors. Option E leverages positional attention dynamics (addressing the "lost in the middle" phenomenon), where LLMs tend to recall and attend most accurately to information positioned at the very beginning (primacy effect) or at the end (recency effect) of the context window. Conversely, dumping uncurated text (Option A) adds noise and consumes quota, repeating instructions excessively (Option C) wastes tokens without improving adherence, and blending documents into an unstructured blob (Option D) obscures citation provenance.
NEW QUESTION # 41
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: C
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 # 42
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