UiPath UiPath-AAAv1 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Agent Blueprint Design | - Workflow decomposition - Agent architecture design |
| Topic 2: Escalations & Human-in-the-Loop | - Action Center workflows - Exception handling and escalation patterns |
| Topic 3: Context Grounding (RAG) | - Retrieval-Augmented Generation concepts - Data grounding strategies |
| Topic 4: Autopilot for Everyone | - Use cases and capabilities - AI-assisted automation building |
| Topic 5: Agentic AI Fundamentals | - Agentic automation concepts - AI agents vs rule-based automation |
| Topic 6: Prompt Engineering for Agents | - System prompts and constraints - Zero-shot and few-shot prompting |
| Topic 7: UiPath Platform Components | - Agent Builder and Orchestrator basics - Studio Web and Autopilot |
| Topic 8: Agentic Evaluations & Governance | - Guardrails and validation logic - LLM-as-a-judge metrics |
| Topic 9: Agent Discovery & Process Assessment | - Identifying automation opportunities - Process suitability for agentic automation |
| Topic 10: Agentic Orchestration (Maestro) | - BPMN-based process design - Workflow orchestration with agents |
UiPath Certified Professional Agentic Automation Associate (UiAAA) Sample Questions:
1. 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) Focus only on complaint categorization and rely on post-processing to handle emotional nuance.
B) Remove detailed task instructions to give the Agent more freedom in interpreting customer messages.
C) Provide vague constraints in an emotional tone.
D) Include explicit context explaining the goal of sentiment analysis and define constraints for identifying urgency.
2. Which statement best describes UiPath Maestro's capability for deploying AI agents within a BPMN-modeled process?
A) Maestro is a workflow engine similar to UiPath Studio, but it only allows you to invoke Agentic and Integration tasks.
B) Maestro deploys only UiPath-built agents in robot-driven processes; any third-party agents must be integrated through external platforms without human checkpoints.
C) Maestro embeds external agents as inline code scripts inside the BPMN file and relies on each provider's runtime instead of Maestro's orchestration engine.
D) Maestro deploys agents from UiPath and external providers-such as LangChain, CrewAI, or Agentforce-through one consistent framework that includes human-in-the-loop orchestration.
3. Why is it important to include examples in prompts?
A) Including examples should only focus on edge cases while ignoring typical scenarios for better variety in results.
B) Carefully chosen examples help guide the agent and improve its ability to generalize across different scenarios.
C) Including examples guarantees output accuracy without any need for further adjustments or refinements.
D) Examples should be omitted to allow the AI to create responses entirely from general knowledge without guidance.
4. What is the significance of the "as-is" process map in identifying agentic automation opportunities?
A) It directly outlines the roles that agents will assume in the optimized process, ensuring alignment with automation requirements.
B) It establishes the goals of the new process, serving as a foundation to later create the "to-be" process map.
C) It serves as a finalized map of processes ready for automation, removing the need for further adjustments or workshops.
D) It defines the current way tasks are performed, helping to highlight inefficiencies, bottlenecks, and areas for improvement that can uncover automation potential.
5. 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) Change every field, including Channel Id, to Variable because an agent cannot infer any field values without explicit arguments.
B) Change every field, including Channel Id, to Argument 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) Declare the field as an output argument in Data Manager so the agent can feed a value back into the tool.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: D | Question # 5 Answer: C |














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