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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Governance, Risk, and Responsible Use | 15% | - Follow organizational AI policies and governance standards - Identify appropriate and inappropriate use cases - Understand ethical implications of Claude use - Apply data sensitivity, regulatory, and privacy considerations |
| Topic 2: Prompting and Task Execution | 14% | - Adapt prompting strategy by task type - Apply task decomposition techniques to structure complex requests - Iterate prompts to improve output quality - Create effective prompts for business and technical tasks |
| Topic 3: Configuration and Knowledge Management | 12% | - Manage uploaded knowledge and connectors - Create effective system-level instructions - Maintain and update configurations - Configure Claude Projects with instructions and knowledge sources |
| Topic 4: Product and Model Selection | 12% | - Align model selection with task requirements - Manage context limitations and memory - Select appropriate Claude product features - Differentiate between Claude model types |
| Topic 5: Troubleshooting and Optimization | 10% | - Adjust approaches based on feedback and results - Optimize workflows for efficiency and effectiveness - Identify and diagnose issues with underperforming prompts or poor outputs |
| Topic 6: Workflow Integration and Solution Design | 16% | - Support solution design through iteration - Integrate Claude into existing workflows and communicate its value and limitations - Analyze requirements and use cases - Use Claude for research, planning, and process optimization |
| Topic 7: Output Evaluation and Validation | 21% | - Identify hallucinations, inconsistencies, and biases in responses - Evaluate Claude-generated outputs for accuracy and completeness - Organize and curate information and select appropriate output formats - Edit and adapt outputs for the intended audience - Apply fact-checking and validation techniques - Determine when human review or additional verification is required |
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NEW QUESTION # 99
An operations assistant is using Claude to support process optimization for an existing intake workflow. The assistant has access to the current process documentation and recent cycle-time data.
Which activity best uses Claude to support this process optimization task?
Answer: D
Explanation:
Under the objective Leverage Claude for research, planning, and process optimization , using Claude for business process re-engineering relies on diagnostic synthesis grounded in empirical operational data.
Option C demonstrates the optimal collaborative use case: ingesting existing process maps alongside actual cycle-time metrics, using Claude's analytical capabilities to locate workflow bottlenecks, delays, and redundancies, and generating structured optimization proposals for human review and decision-making.
Relying on generic, ungrounded industry templates (Option A) overlooks internal operational context.
Expecting Claude to calculate exact cycle-time reductions deterministically (Option B) misuses LLMs for predictive queuing simulations. Replacing human stakeholder interviews with simulated automated AI interactions (Option D) produces ungrounded assumptions and fails change management standards.
NEW QUESTION # 100
You are a content creator. A first response from Claude is accurate but uses inconsistent terminology that does not match your organization's glossary.
Which iterative change addresses the issue most directly?
Answer: A
Explanation:
Under the objective Iterate prompts to improve output quality (Domain 1: Prompting and Task Execution), resolving domain-specific vocabulary inconsistencies requires grounding the prompt with explicit terminology constraints.
When Claude generates accurate conceptual content but uses generic or non-standard synonyms, the most direct prompt refinement is providing the organization's canonical terminology glossary (or uploading it to Project knowledge) accompanied by a strict constraint instructing the model to use only those defined terms (Option D). This eliminates vocabulary drift and guarantees brand consistency. Expanding prompt length (Option A) amplifies terminology discrepancies. Encouraging invented terms (Option B) worsens terminology alignment. Deleting topics from the prompt (Option C) fails the original task requirements.
NEW QUESTION # 101
You are a project manager working through a long planning conversation with Claude and must keep the conversation productive as it grows.
Which two practices keep a long planning conversation productive? (Select two.) Each correct answer presents a complete solution.
Answer: A,C
Explanation:
Under the objective Understand, manage context limitations and memory considerations and when to restart, summarize, or persist , managing conversational state across long planning sessions is essential for maintaining output quality and coherence. Large Language Models operate within finite context windows where attention can degrade as extraneous tokens accumulate.
Option B is a best practice because shifting subtopics often dilutes earlier instructions; explicitly restating key constraints and strategic goals ensures the model anchors its attention on active parameters without being distracted by obsolete conversational turns. Option C represents context compression-a core technique where key milestones, agreed parameters, and decisions are consolidated into a dense summary. This reduces token overhead, frees up working memory, and prevents hallucination or drift. Conversely, opening a new thread for every minor question (Option A) fractures contextual continuity, switching topics arbitrarily (Option D) pollutes attention heads, and avoiding summarization (Option E) accelerates context bloat and degrades performance.
NEW QUESTION # 102
As part of a workflow redesign, a process analyst is applying the AI Fluency Framework Delegation competency.
Which two criteria most directly inform Delegation decisions? (Select two.)
Answer: D,E
Explanation:
Options B and E are correct because Delegation requires evaluating both the capabilities needed for a task and the risk created by assigning it to AI. Anthropic defines Delegation as thoughtfully deciding which work should be completed by a human, performed collaboratively, or handled independently by AI. Tasks requiring distinctly human empathy, creativity, contextual judgment, accountability, or value-based decisions are less suitable for complete delegation. Claude may assist, but a human should retain control of the consequential decision.
Reversibility and error consequences are also critical. A low-impact, easily checked draft can generally receive more AI autonomy than an irreversible action or a decision that could materially affect people.
Anthropic's research on workplace AI use similarly reports that employees tend to delegate tasks that are low- stakes and readily verifiable while applying active supervision to high-stakes work.
Workflow age, diagram complexity, and employee seniority are indirect characteristics; they do not establish whether Claude has the required capabilities or whether an error can be safely corrected. An old workflow can still contain unsuitable tasks, and a junior employee may perform highly sensitive work. Thus, B and E provide the most relevant task-level and risk-level criteria. See Anthropic's Delegation lesson and research on workplace AI delegation .
NEW QUESTION # 103
You are a senior analyst using Claude to analyze requirements from several stakeholder sources.
Which is the correct order of steps?
(1) Group related requirements and flag conflicts or ambiguities for stakeholder review.
(2) Validate the structured output against the original sources for accuracy and completeness.
(3) Submit the consolidated inputs to Claude with a structured extraction prompt.
(4) Gather and label the source materials so each requirement can be traced.
(5) Document the final requirements set with source traceability and status.
Answer: C
Explanation:
Option D is correct: 4, 1, 3, 2, 5. First, gather and label the source materials so every requirement can be traced to a stakeholder interview, process document, or other authoritative input. Second, organize related material and identify apparent conflicts or ambiguities. This preparation prevents unrelated statements from being blended and highlights issues that Claude should preserve rather than silently resolve.
Third, submit the consolidated material using a structured extraction prompt that defines the requested fields, such as requirement identifier, statement, source, owner, priority, ambiguity, and status. Anthropic's prompting guidance emphasizes clear instructions, contextual information, and explicit output formats.
Fourth, validate Claude's structured output against the original sources. This step is essential because a well- formatted answer can still omit, distort, or combine requirements. Anthropic recommends auditable citations and verification against supporting text, retracting claims that cannot be grounded.
Finally, document the approved requirements set with traceability and resolution status. Options A and C begin analysis or prompting before the sources have been properly gathered and labelled. The missing text in Option B cannot establish a valid alternative, so it has been preserved as missing rather than invented. This sequence combines task decomposition with source-grounded validation. See Anthropic's prompting best practices and hallucination-reduction guidance .
NEW QUESTION # 104
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