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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prompting and Task Execution | 14% | - Iterating prompts to improve output - Creating effective prompts - Adapting prompting strategies to task types - Task decomposition |
| Topic 2: Governance, Risk, and Responsible Use | 15% | - Ethical and responsible AI use - Identifying appropriate and inappropriate AI use cases - Organizational AI governance and policies - Data sensitivity, privacy, and regulatory considerations |
| Topic 3: Product and Model Selection | 12% | - Balancing quality, speed, and cost - Selecting appropriate Claude product features - Selecting Claude models - Managing context limitations and memory |
| Topic 4: Workflow Integration and Solution Design | 16% | - Analyzing requirements and use cases - Integrating Claude into existing workflows - Communicating Claude's value and limitations - Solution design and iteration - Research, planning, and process optimization |
| Topic 5: Troubleshooting and Optimization | 10% | - Adjusting approaches based on feedback and results - Optimizing workflows for efficiency and effectiveness - Diagnosing underperforming prompts and outputs |
| Topic 6: Output Evaluation and Validation | 21% | - Fact-checking and validation - Evaluating output accuracy and completeness - Determining when human review or verification is required - Identifying hallucinations, inconsistencies, and bias - Editing, adapting, and refining outputs |
| Topic 7: Configuration and Knowledge Management | 12% | - Maintaining configuration and knowledge sources - Managing uploaded knowledge and connectors - Managing instructions and knowledge sources - Configuring Claude Projects |
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NEW QUESTION # 54
A finance consultant is adapting a Claude-generated narrative for a quarterly investor update. Investors have a fixed time window for the call and expect the headline result and forward outlook to be clear early.
Which adaptation is most appropriate for this audience?
Answer: B
Explanation:
Under the objective Edit, adapt, refine, and compare the output generated by Claude model(s) for the intended audience (Domain 2: Output Evaluation and Validation), adapting generated text requires restructuring content to match the executive decision-making style of the stakeholders.
Executive and investor audiences operate under strict time constraints and prioritize the bottom-line financial outcome before examining underlying mechanics (following the Minto Pyramid / Bottom-Line-Up-Front principle). Option C correctly structures the executive narrative: opening immediately with the headline financial figures, following with a concise breakdown of key operational drivers, and concluding with forward-looking guidance. Structuring the briefing chronologically (Option D) or burying core financial results in the middle of operational prose (Option A) creates cognitive friction and wastes time. Leading with the forward outlook before establishing current financial performance (Option B) lacks context.
NEW QUESTION # 55
You are a research associate preparing inputs for a long task that references two lengthy regulatory documents, but only specific sections apply.
Which approach best preserves context-window capacity?
Answer: C
Explanation:
Option A is correct because Claude's context window is finite and must accommodate the system instructions, conversation history, documents, tool results, the current request, and the generated response. Anthropic specifically cautions that more context is not automatically better: as unnecessary content accumulates, relevant details may become harder to retrieve and accuracy can decline through "context rot." Curating the context is therefore as important as its total capacity.
Extracting only the applicable regulatory sections preserves the authoritative language needed for the task while removing unrelated chapters that consume tokens and distract from the relevant requirements. The extracts should retain headings, section identifiers, effective dates, and source labels so Claude's conclusions remain traceable. Option B wastes capacity and may reduce focus. Option C destroys meaningful semantic structure and creates an unusable interaction pattern. Option D removes the grounding evidence entirely and invites hallucination, which is especially inappropriate for regulatory analysis.
For long documents, Anthropic also recommends grounding claims in direct quotations and citations. Thus, the strongest approach is to provide carefully selected, clearly labelled excerpts and require Claude to trace material claims to them. See Anthropic's documentation on context windows and reducing hallucinations .
NEW QUESTION # 56
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 # 57
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: C
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 # 58
You are a knowledge worker evaluating which Claude feature matches each proposed use case.
Which two feature-to-use-case matches are appropriate? (Select two.)
Each correct answer presents a complete solution.
Answer: C,E
Explanation:
Options A and E correctly match capabilities to tasks. A quarterly report derived from many documents benefits from Claude's long-context processing because the model must review, connect, and synthesize information distributed across numerous sources. The user should organize the sources clearly, identify the required reporting structure, and verify that the resulting report accurately represents the inputs.
A complex multistep pricing calculation should use a calculator or code-execution capability. Language models can reason about a calculation's structure, but deterministic computation tools provide stronger numerical reliability and make intermediate operations easier to inspect. The human reviewer should still verify inputs, formulas, units, and business rules.
Option B does not require long-context processing because a single short email can ordinarily be handled within a basic chat request. Option C unnecessarily invokes web search for a stable, established mathematical formula that can be supplied directly or calculated with an appropriate tool. Option D mismatches a numerical tool with a language-editing task; rewriting a description in simpler language is a core text-generation capability and does not require a calculator.
Effective feature selection means matching the task's actual bottleneck-context capacity, external information retrieval, deterministic computation, or reusable content creation-to the capability designed to address it.
NEW QUESTION # 59
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