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| Section | Weight | Objectives |
|---|---|---|
| Workflow Integration and Solution Design | 16% | - Communicating Claude's value and limitations - Solution design and iteration - Integrating Claude into existing workflows - Analyzing requirements and use cases - Research, planning, and process optimization |
| Troubleshooting and Optimization | 10% | - Adjusting approaches based on feedback and results - Optimizing workflows for efficiency and effectiveness - Diagnosing underperforming prompts and outputs |
| Output Evaluation and Validation | 21% | - Evaluating output accuracy and completeness - Editing, adapting, and refining outputs - Determining when human review or verification is required - Identifying hallucinations, inconsistencies, and bias - Fact-checking and validation |
| Product and Model Selection | 12% | - Balancing quality, speed, and cost - Managing context limitations and memory - Selecting Claude models - Selecting appropriate Claude product features |
| Governance, Risk, and Responsible Use | 15% | - Data sensitivity, privacy, and regulatory considerations - Identifying appropriate and inappropriate AI use cases - Organizational AI governance and policies - Ethical and responsible AI use |
| Prompting and Task Execution | 14% | - Iterating prompts to improve output - Task decomposition - Creating effective prompts - Adapting prompting strategies to task types |
| Configuration and Knowledge Management | 12% | - Managing uploaded knowledge and connectors - Maintaining configuration and knowledge sources - Configuring Claude Projects - Managing instructions and knowledge sources |
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NEW QUESTION # 35
You are a project manager at Orinexa, Inc. You are picking a Claude model for a new production workload and must complete the requirements steps before testing candidates.
Which two steps must be completed BEFORE testing candidate models on a representative sample? (Select two.) Each correct answer presents part of the solution.
Answer: C,D
Explanation:
Under the objective Align model selection with task requirements (e.g., cost, speed, quality) , model evaluation follows a structured engineering workflow prior to benchmark testing.
Before running comparative empirical tests on a representative sample dataset, the team must first establish evaluation criteria: defining the required output quality bar, maximum acceptable latency, throughput targets, and budget constraints (Option A). Next, the team maps those requirements against known model family characteristics (Haiku, Sonnet, Opus) to select the appropriate candidate models for testing (Option C). Once requirements are set and candidates selected, empirical sample testing can proceed. Promoting models to production (Option D), securing final platform/security rollout sign-offs (Option E), and ongoing regression testing for new model releases (Option B) are downstream deployment activities that occur after testing is completed.
NEW QUESTION # 36
You are an operations lead choosing actions when a Claude conversation has degraded in quality.
Which recovery action should be tried first when conversation quality degrades?
Answer: A
Explanation:
Answer A is correct. When a long Claude conversation begins producing less relevant, inconsistent, or lower- quality responses, the first recovery action should be to consolidate the important context. A concise summary should capture the current objective, confirmed decisions, applicable constraints, authoritative facts, unfinished tasks, and required output format. The user can then provide a focused follow-up prompt that clearly states the next action.
This approach removes accumulated conversational noise while preserving useful progress. Long conversations may contain obsolete instructions, abandoned ideas, corrections, and competing requirements that make the current task harder to interpret. A structured summary re-establishes a clean working state without unnecessarily restarting the entire process.
Option B is disproportionate because changing vendors does not diagnose or correct poor context management. Option C adds unnecessary escalation before basic recovery has been attempted. Option D may eventually be appropriate when the conversation is irreparably confused, but immediately discarding all work wastes valid context and completed analysis.
Anthropic's prompting guidance emphasizes clear instructions, relevant context, structured inputs, and explicit task requirements. Summarizing the state and narrowing the next request applies these principles directly. If quality remains poor after this step, the user can then start a new conversation using the summary as its initial context. Anthropic prompting best practices
NEW QUESTION # 37
You are an operations lead evaluating prompting strategies that teammates have proposed for various task types.
Which two strategies represent appropriate matches between strategy and task type? (Select two.) Each correct answer presents part of the solution.
Answer: B,E
Explanation:
Under the objective Adapt prompting strategies based on task type (e.g., analysis, research, drafting, brainstorming) , prompting architectures must match the operational nature and variability of the task.
Option C correctly pairs open, exploratory prompting with divergent brainstorming and early-stage strategy, allowing Claude the flexibility to generate wide-ranging perspectives, identify unexpected market angles, and propose creative concepts. Option E correctly pairs rigid, templated prompting (with explicit constraints, schema definitions, and validation rules) with recurring compliance reporting, where deterministic output structure, consistency, and adherence to regulatory schemas are mandatory. Conversely, applying rigid templates to creative ideation (Option A) constrains creativity, using open exploration for contract redlining (Option B) risks hallucination and missed clauses, and enforcing rigid schemas on informal unformatted feedback (Option D) creates unnecessary rigidity.
NEW QUESTION # 38
A project manager is evaluating a proposal to use Claude to autonomously approve refunds above a defined threshold without human review. The volume is high-roughly 2,000 refunds per week-the average refund amount is moderate, and a small percentage of refunds in historical audits required correction. The team needs to reduce cycle time.
Which response is most appropriate?
Answer: A
Explanation:
Option B provides the strongest balance between operational efficiency and proportionate human oversight.
The historical correction rate demonstrates that Claude's output cannot safely be treated as uniformly reliable, while the high weekly volume makes universal manual processing unnecessarily inefficient. A risk-based triage design allows clearly defined, low-value, reversible cases to proceed through tightly controlled automation while routing ambiguous or higher-impact cases to accountable human decision-makers.
The classification rules must be explicit and independently tested. Relevant factors could include refund amount, unusual transaction history, policy exceptions, disputed facts, suspected fraud, and the confidence or completeness of the available evidence. Standard cases would remain subject to human approval, while high- risk cases would receive supervisor review.
Options A and C rely primarily on retrospective sampling. That approach may detect patterns of errors, but it does not prevent an incorrect refund from being issued in an individual case. Option D preserves strong oversight but requires manual approval for every transaction, failing to use risk differentiation to address the cycle-time problem.
Claude should augment the workflow through classification, evidence gathering, and recommendation.
Human authority must remain at the points where uncertainty, financial impact, or policy exceptions make an error more consequential.
NEW QUESTION # 39
You are a customer-success manager considering whether to escalate a Claude-generated response.
Which factor most strongly raises the impact of the output and supports escalation before external use?
Answer: A
NEW QUESTION # 40
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