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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Output Evaluation and Validation | 21% | - Editing, adapting, and refining outputs - Determining when human review or verification is required - Identifying hallucinations, inconsistencies, and bias - Evaluating output accuracy and completeness - Fact-checking and validation |
| Topic 2: Prompting and Task Execution | 14% | - Task decomposition - Creating effective prompts - Iterating prompts to improve output - Adapting prompting strategies to task types |
| Topic 3: Product and Model Selection | 12% | - Selecting appropriate Claude product features - Selecting Claude models - Balancing quality, speed, and cost - Managing context limitations and memory |
| Topic 4: Governance, Risk, and Responsible Use | 15% | - Identifying appropriate and inappropriate AI use cases - Data sensitivity, privacy, and regulatory considerations - Organizational AI governance and policies - Ethical and responsible AI use |
| Topic 5: Configuration and Knowledge Management | 12% | - Managing uploaded knowledge and connectors - Managing instructions and knowledge sources - Configuring Claude Projects - Maintaining configuration and knowledge sources |
| Topic 6: Workflow Integration and Solution Design | 16% | - Analyzing requirements and use cases - Solution design and iteration - Research, planning, and process optimization - Communicating Claude's value and limitations - Integrating Claude into existing workflows |
| Topic 7: Troubleshooting and Optimization | 10% | - Optimizing workflows for efficiency and effectiveness - Diagnosing underperforming prompts and outputs - Adjusting approaches based on feedback and results |
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NEW QUESTION # 108
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 # 109
You are an analyst working on a one-off complex problem that genuinely requires multi-step reasoning over an extended chain of thought.
Which model is best suited to this work?
Answer: A
Explanation:
Among the choices provided, Opus is the appropriate model for a complex, one-off problem requiring sustained, multi-step reasoning. Opus models are designed for advanced analysis, demanding knowledge work, complex tool use, and long-horizon tasks. The additional capability is justified because the workload explicitly prioritizes reasoning quality rather than minimum latency or cost.
Option A incorrectly treats lightweight models as universally preferable. Haiku is optimized for speed and cost-sensitive, straightforward workloads, but that does not make it the best choice for every complex problem. Option B ignores genuine capability and reasoning differences between model tiers. Option D is false because the Claude lineup includes models designed for difficult reasoning tasks.
The current Claude portfolio has evolved and now includes additional high-capability models, but Opus remains the strongest valid selection among the listed answers. In production, the analyst should test representative cases and compare accuracy, latency, and cost rather than choosing solely by tier name. For this explicitly complex one-off task, however, higher reasoning capability is the dominant requirement.
Anthropic describes Opus as suited to complex analysis, enterprise work, advanced research, and deep reasoning. Anthropic's model-selection guidance
NEW QUESTION # 110
You are setting up a Connector for a shared data source that several colleagues will use.
Which Connector setup step should be performed first?
Answer: A
Explanation:
Option D is the necessary first step because authorization and data suitability must be established before the shared source is connected to Claude. The team should verify that the connector and its provider are approved under organizational AI, security, procurement, and privacy policies. It must also determine the source's data classification and whether information in that source may legally and contractually be processed through the connector.
Connecting the source first, as proposed in Option C, could expose restricted information before governance review has occurred. Testing a representative task under Option B likewise assumes that access has already been approved. Documenting the connector's purpose and suitable use cases under Option A is important, but that operational documentation should follow the initial determination that the connector and relevant data are permitted.
After approval, the team can connect the source using an account with appropriate permissions, verify authentication, test access boundaries, and confirm that Claude retrieves only information available to the authenticated user. The team should then document approved use cases, prohibited data, human-review requirements, and reporting procedures. This sequence follows least-privilege and data-governance principles and avoids treating successful authentication as evidence that a connector is organizationally authorized or suitable for every type of information.
NEW QUESTION # 111
You are an operations lead sorting proposed Claude use cases by whether they are acceptable for your team to pursue.
Which two proposed use cases are acceptable for the team to pursue with Claude? (Select two.) Each correct answer presents a complete solution.
Answer: C,D
Explanation:
Options A and E are the most appropriate because they describe bounded, reviewable tasks using approved information for low-risk internal analysis or content preparation. In option A, Claude summarizes authorized internal documentation rather than making consequential decisions. In option E, Claude identifies aggregate themes under established data-handling rules, allowing humans to examine the results before using them.
Option B involves sensitive health information and could affect clinical reasoning. Even when a clinician reviews the result, using Claude for patient-related diagnostic support requires explicit organizational authorization, suitable privacy controls, and domain-specific safeguards that the scenario does not establish.
Option C similarly involves professional legal work and client-facing material. Attorney review is helpful but does not, by itself, establish that the system, data handling, and workflow have been approved for legal use.
Option D is inappropriate because promotion decisions are consequential employment decisions. Claude may assist with authorized administrative tasks, but it should not determine who receives employment opportunities or materially influence such decisions without stringent governance and meaningful human accountability.
The key distinction is not merely whether a person reviews the output. Appropriate selection also depends on data sensitivity, potential harm, organizational authorization, applicable policies, and whether Claude is assisting with a reversible task or influencing a high-impact decision.
NEW QUESTION # 112
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: D,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 # 113
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