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| Section | Weight | Objectives |
|---|---|---|
| Governance, Risk, and Responsible Use | 15% | - Identify appropriate and inappropriate use cases - Understand ethical implications of Claude use - Apply data sensitivity, regulatory, and privacy considerations - Follow organizational AI policies and governance standards |
| Configuration and Knowledge Management | 12% | - Create effective system-level instructions - Configure Claude Projects with instructions and knowledge sources - Manage uploaded knowledge and connectors - Maintain and update configurations |
| Output Evaluation and Validation | 21% | - Identify hallucinations, inconsistencies, and biases in responses - Organize and curate information and select appropriate output formats - Edit and adapt outputs for the intended audience - Apply fact-checking and validation techniques - Evaluate Claude-generated outputs for accuracy and completeness - Determine when human review or additional verification is required |
| Product and Model Selection | 12% | - Manage context limitations and memory - Differentiate between Claude model types - Select appropriate Claude product features - Align model selection with task requirements |
| Prompting and Task Execution | 14% | - Create effective prompts for business and technical tasks - Apply task decomposition techniques to structure complex requests - Iterate prompts to improve output quality - Adapt prompting strategy by task type |
| Troubleshooting and Optimization | 10% | - Adjust approaches based on feedback and results - Identify and diagnose issues with underperforming prompts or poor outputs - Optimize workflows for efficiency and effectiveness |
| Workflow Integration and Solution Design | 16% | - Integrate Claude into existing workflows and communicate its value and limitations - Support solution design through iteration - Use Claude for research, planning, and process optimization - Analyze requirements and use cases |
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NEW QUESTION # 67
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: A,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 # 68
A knowledge worker is briefing a stakeholder group on Claude's limitations. The stakeholders will use Claude on customer-facing work where confident-sounding output that contains errors would cause real harm.
Which limitation is most important to communicate clearly?
Answer: A
Explanation:
Under the objective Communicate Claude's value and limitations to stakeholders , managing risk in customer-facing applications requires transparently communicating the phenomenon of confident hallucinations.
Large Language Models generate text via probabilistic pattern matching, meaning they can produce articulate, authoritative, and linguistically polished output that nevertheless contains completely fabricated or unverified claims (Option B). In customer-facing workflows where misinformation causes commercial, legal, or brand harm, stakeholders must understand that surface fluency is not a proxy for factual truth, making rigorous human-in-the-loop review mandatory. While training cutoffs (Option D) and response variation (Option A) are operational realities, the primary risk for customer harm stems from unverified, confident-sounding hallucinations escaping human review. Response verbosity (Option C) is merely a cosmetic usability preference.
NEW QUESTION # 69
You are an operations lead integrating Claude into a multi-person team workflow.
Which integration step should be performed first?
Answer: C
Explanation:
Under the objective Integrate Claude into existing workflows to augment or redesign workflows , successful AI adoption requires structured process mapping prior to implementation, piloting, or scaling.
The foundational first step (Option A) is conducting task decomposition and interface analysis: analyzing the existing workflow to determine exact stages where Claude provides tangible leverage (e.g., synthesis, drafting, data categorization) versus stages that mandate human decision-making, verification, and sign-off (human-in-the-loop handoffs). Attempting to run a pilot (Option B), iterate based on pilot metrics (Option C), or author final training documentation (Option D) before defining the functional boundaries and handoff architecture results in unstructured trials, unclear accountability, and higher operational risk.
NEW QUESTION # 70
While preparing stakeholder communication about a proposed Claude use case, a senior manager is applying the AI Fluency Framework Description competency.
Which framing best reflects Description principles for stakeholder communication?
Answer: D
Explanation:
Option C is correct because effective Description communicates the intended product, process, and collaborative expectations accurately. Stakeholders need to know what Claude will do, what inputs it requires, which outputs it can produce reliably, where errors or limitations may occur, and which decisions or reviews remain under human ownership. The explanation should be calibrated to the audience: executives may need business value and risk boundaries, while operational or technical users may require workflow details and validation requirements.
Option A conceals a material governance control and could lead stakeholders to misunderstand Claude's autonomy. Option B is not responsible simply because it is conservative; systematically understating capabilities can produce poor decisions and unjustified resistance. Option D is plainly inappropriate because exaggerated claims create unrealistic expectations and weaken informed oversight.
Anthropic defines Description as effectively communicating goals to produce useful AI behaviour and outputs. Its guidance distinguishes Product Description, Process Description, and Performance Description.
Transparent stakeholder framing also supports Diligence by preserving accountability for how AI is represented and used. Therefore, balanced communication about capabilities, limitations, and human oversight is the only defensible framing. See Anthropic's AI Fluency Description lesson and AI Fluency Framework .
NEW QUESTION # 71
You are sorting Claude output structural defects by which most undermines clarity.
Which structural defect most severely undermines the clarity of the output?
Answer: B
Explanation:
Under the objective Identify hallucinations, inconsistencies, and biases in responses , evaluating output quality requires distinguishing between cosmetic formatting imperfections and critical semantic contradictions.
A contradiction between the central conclusion and the supporting factual evidence in the body (Option D) represents a critical structural and logical breakdown. This defect directly destroys the internal consistency, credibility, and actionable utility of the deliverable, potentially misleading stakeholders and causing operational errors. In contrast, unequal subheading lengths (Option A), minor cosmetic typos (Option C), or slight terminology drift across paragraphs (Option B) represent surface-level stylistic flaws that can be quickly edited without fundamentally invalidating the underlying message of the artifact.
NEW QUESTION # 72
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