Last Updated: Aug 18, 2026
No. of Questions: 61 Questions & Answers with Testing Engine
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| Section | Objectives |
|---|---|
| Topic 1: Agent Discovery & Process Assessment | - Identifying automation opportunities - Process suitability for agentic automation |
| Topic 2: Agentic AI Fundamentals | - Agentic automation concepts - AI agents vs rule-based automation |
| Topic 3: Prompt Engineering for Agents | - Zero-shot and few-shot prompting - System prompts and constraints |
| Topic 4: Escalations & Human-in-the-Loop | - Action Center workflows - Exception handling and escalation patterns |
| Topic 5: Agentic Evaluations & Governance | - LLM-as-a-judge metrics - Guardrails and validation logic |
| Topic 6: UiPath Platform Components | - Agent Builder and Orchestrator basics - Studio Web and Autopilot |
| Topic 7: Autopilot for Everyone | - AI-assisted automation building - Use cases and capabilities |
| Topic 8: Context Grounding (RAG) | - Data grounding strategies - Retrieval-Augmented Generation concepts |
| Topic 9: Agentic Orchestration (Maestro) | - BPMN-based process design - Workflow orchestration with agents |
| Topic 10: Agent Blueprint Design | - Agent architecture design - Workflow decomposition |
1. How does adjusting the "Number of results" setting affect the agent's use of context from indexes?
A) It selects which Orchestrator folder to use, determining the location of stored workflows and deciding which set of predefined rules will apply during data retrieval and processing.
B) It modifies the similarity threshold for chunk retrieval and lowers the number of tokens used.
C) It changes the number of chunks returned, impacting both the size of the grounding payload and the filtering of relevant information.
D) It makes the agent ignore all context completely, resulting in outputs that are entirely disconnected from the indexed data, regardless of its relevance to the query or prompt provided.
2. Which of the following is an essential aspect of crafting a comprehensive agent story during the validation stage?
A) Brainstorming automation use cases without validating personas or critically evaluating existing processes, focusing purely on agent capabilities.
B) Starting immediately with agent behavior prototyping using tools like the Agents designer canvas in Studio Web without assessing mapped automations or impacted systems.
C) Generalizing automation opportunities across all processes and roles without tailoring solutions based on specific personas or organizational contexts.
D) Understanding the daily pain points and inefficiencies of the selected role to identify tasks that consume unnecessary time and potential gains from agent intervention.
3. A company is integrating an Agent into its customer support workflow to detect sentiment and classify complaints (e.g., "Billing issue", "Product defect"). However, the Agent's responses often miss subtle emotional cues like frustration or urgency. What change to the prompt design would most improve the quality of sentiment detection?
A) Include explicit context explaining the goal of sentiment analysis and define constraints for identifying urgency.
B) Focus only on complaint categorization and rely on post-processing to handle emotional nuance.
C) Remove detailed task instructions to give the Agent more freedom in interpreting customer messages.
D) Provide vague constraints in an emotional tone.
4. While configuring an Integration Service activity as a tool for your agent in Studio Web, how should you set up the activity so the agent can decide the value of a required field (e.g. Channel Id) at runtime based solely on instructions in the prompt?
A) Declare the field as an output argument in Data Manager so the agent can feed a value back into the tool.
B) Change every field, including Channel Id, to Variable because an agent cannot infer any field values without explicit arguments.
C) Leave the field's input method on Prompt (the default) and keep or refine the tool description; this lets the agent infer the value during execution.
D) Change every field, including Channel Id, to Argument because an agent cannot infer any field values without explicit arguments.
5. Which of the following best describes how agents handle dynamic environments?
A) Agents fail to execute tasks when information or processes change.
B) Agents adapt to changing conditions by learning.
C) Agents require complete human assistance whenever processes change.
D) Agents rely solely on static rules without contextual learning.
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: D | Question # 3 Answer: A | Question # 4 Answer: C | Question # 5 Answer: B |
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