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UiPath Certified Professional - General Track UiPath Certified Professional Agentic Automation Associate (UiAAA)

UiPath Certified Professional Agentic Automation Associate (UiAAA)

Last Update Feb 17, 2026
Total Questions : 60

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Questions 2

A team is designing an agent to convert plain text meeting notes into a formatted agenda (e.g., structured bullet points). Despite providing a few example transformations in the prompt, the agent generates agendas in inconsistent formats. What critical step was likely overlooked?

Options:

Adding clear instructions detailing the output format.

Including constraints to limit the length of the agenda for simplicity.

Adding randomized formatting examples to test the agent's creativity.

Providing only examples without additional context about the task.

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Questions 3

A company launches a marketing campaign powered by generative AI and agentic AI technologies. What best describes how their roles differ?

Options:

Generative AI produces outputs like text or images, while agentic AI focuses on intelligent automation, decision-making, and dynamic task execution.

Generative AI focuses on improving customer sentiment analysis, while agentic AI refines campaign content.

Both generative AI and agentic AI collaborate to create promotional materials.

Agentic AI designs campaign materials, while generative AI handles customer queries in real-time.

Discussion 0

Questions 4

What is the primary role of guardrails in tools?

Options:

Guardrails are used exclusively to automate all tool corrections without the possibility of triggering human intervention.

Guardrails control unexpected behaviors within tool calls deterministically, allowing developers to configure conditions for human intervention and escalations.

Guardrails are designed to apply only after tool execution, without influencing pre-execution conditions.

Guardrails only validate tool inputs during development and do not address unpredictable behaviors at runtime.

Discussion 0

Questions 5

A developer is implementing a few-shot structured prompt for an email classification task. The prompt includes examples of email subjects labeled with their respective classifications, such as "Spam" or "Work." What is the most important aspect to consider when selecting examples for the prompt?

Options:

Include examples with intentionally incorrect labels to improve training.

Always use more than 10 examples, regardless of task complexity.

Choose examples that are diverse, relevant, and typical of the task's expected input.

Use random and unrelated examples to test the prompt's robustness.

Discussion 0

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