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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Troubleshooting and Optimization | 10% | - Optimizing workflows for efficiency and effectiveness - Diagnosing underperforming prompts and outputs - Adjusting approaches based on feedback and results |
| Topic 2: Prompting and Task Execution | 14% | - Iterating prompts to improve output - Creating effective prompts - Adapting prompting strategies to task types - Task decomposition |
| Topic 3: Product and Model Selection | 12% | - Selecting appropriate Claude product features - Balancing quality, speed, and cost - Managing context limitations and memory - Selecting Claude models |
| Topic 4: Configuration and Knowledge Management | 12% | - Managing uploaded knowledge and connectors - Maintaining configuration and knowledge sources - Configuring Claude Projects - Managing instructions and knowledge sources |
| Topic 5: Output Evaluation and Validation | 21% | - Identifying hallucinations, inconsistencies, and bias - Fact-checking and validation - Determining when human review or verification is required - Editing, adapting, and refining outputs - Evaluating output accuracy and completeness |
| Topic 6: Governance, Risk, and Responsible Use | 15% | - Data sensitivity, privacy, and regulatory considerations - Organizational AI governance and policies - Identifying appropriate and inappropriate AI use cases - Ethical and responsible AI use |
| Topic 7: Workflow Integration and Solution Design | 16% | - Solution design and iteration - Analyzing requirements and use cases - Research, planning, and process optimization - Communicating Claude's value and limitations - Integrating Claude into existing workflows |
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NEW QUESTION # 12
You are reviewing a Claude-generated competitor brief for unsupported claims.
Which is the correct order of review steps?
(1) Cross-check each specific claim against the supplied source material or trusted external references.
(2) Decide whether to correct, re-prompt, or escalate based on the findings.
(3) Document each unsupported or inconsistent claim with its location and severity.
(4) Identify the specific factual claims, statistics, and citations in the brief.
(5) Read the brief from beginning to end and flag any claims that feel surprising.
Answer: D
Explanation:
Answer C is correct. A defensible fact-check begins with a complete reading of the brief (5), which reveals its overall argument and flags surprising or unusually confident assertions. The reviewer then identifies the concrete factual claims, statistics, and citations that can actually be tested (4). Those items are checked against supplied evidence or trustworthy external sources (1). Any unsupported, contradictory, or inaccurate claim is then recorded with its location and severity (3), creating a usable audit trail. Only after the evidence is assembled should the reviewer decide whether to correct the text, re-prompt Claude, or escalate the issue (2).
This produces the sequence 5, 4, 1, 3, 2. Option D reverses the first two activities, while Options A and B attempt verification before a proper claim inventory exists. Anthropic's guidance recommends structured research, explicit success criteria, and verification across sources; the AI Fluency framework's Discernment and Diligence competencies also keep evaluation and accountability with the human reviewer. The PDF marks D, but that order is weaker and should be corrected to C. Anthropic prompting best practices
NEW QUESTION # 13
A learning specialist is configuring a Claude Project for a recurring course-design workflow.
Which configuration approach best leverages a Skill alongside other Project elements?
Answer: B
Explanation:
Under the objective Configure Claude Projects with instructions and knowledge sources (Domain 5:
Configuration and Knowledge Management), maximizing the utility of Claude Projects involves harmonizing all built-in platform capabilities: custom instructions, knowledge bases, and specialized Skills.
Option B exemplifies an integrated configuration: packaging procedural execution logic into a Project Skill, uploading pedagogical frameworks and curriculum standards to Project knowledge, and authoring system instructions that explicitly define how Claude should utilize the Skill in conjunction with the knowledge repository. In contrast, creating contradictory instructions (Option A) causes prompt collisions and erratic behavior. Disabling skills (Option C) forces repetitive manual prompt engineering in every chat. Omitting supporting reference knowledge and system instructions (Option D) leaves the Project ungrounded and under- configured.
NEW QUESTION # 14
A communications manager is drafting a prompt for Claude to produce a quarterly newsletter for store managers in three regions. The agreed key messages, regional details, and a prior newsletter the team liked are all available.
Which prompt approach is most likely to produce a usable first draft?
Answer: B
Explanation:
Under the objective Create effective prompts for business and technical tasks , Anthropic's core prompt engineering principle emphasizes being explicit, direct, and providing complete structural constraints rather than relying on implicit document matching.
Option D establishes all essential prompt components directly within the prompt itself: explicitly defining the target audience (store managers), geographic scope (three regions), length constraints, tone guidelines, and the core messaging points, while treating the historical newsletter as a calibrated few-shot tone reference. This explicit framing eliminates ambiguity and prevents the model from copying obsolete structure or irrelevant sections from the historical document. In contrast, Option A relies excessively on broad pattern-matching against an attachment without providing explicit parameter boundaries in the prompt body. Option B lacks structural and tonal detail, while Option C delegates tone and length decisions entirely to the model.
NEW QUESTION # 15
Your conversation context has grown long, and the model is producing inconsistent outputs.
Which context-management step should be performed first?
Answer: C
Explanation:
Option C is the appropriate first step because summarization compresses a lengthy and potentially conflicting conversation into a clear working state. The summary should retain the current objective, confirmed decisions, relevant facts, active constraints, required output format, unresolved questions, and the next action Claude must perform. Obsolete instructions, rejected alternatives, and repetitive discussion should be removed.
Option A does not directly address the cause of the inconsistency. A more capable model may still struggle when the conversation contains conflicting requirements or excessive irrelevant material. Option B provides no corrective action and allows the context problem to continue. Option D may eventually be necessary, but immediately moving to a new conversation risks losing important information or reproducing the same confusion if the essential context has not first been identified.
After producing the summary, the user should compare it with the original requirements and correct any omissions. The validated summary can then be reasserted in the current conversation. If performance remains inconsistent, it can serve as the starting context for a new chat. This staged approach preserves useful progress while reducing context noise and limiting unnecessary repetition.
NEW QUESTION # 16
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: B
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 # 17
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