Learn with UiPath : UiPath-AAPv1 training material for 100% pass
Updated: Nov 12, 2026
No. of Questions: 108 Questions & Answers with Testing Engine
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UiPath UiPath-AAPv1 Exam Overview:
| Certification Vendor: | UiPath |
|---|---|
| Exam Name: | UiPath Agentic Automation Professional Exam |
| Exam Number: | UiPath-AAPv1 |
| Exam Price: | USD 300 (plus any applicable taxes) |
| Certificate Validity Period: | 3 years from the date of credential achievement |
| Exam Format: | Multiple-choice, Sequencing, Drag-and-drop |
| Available Languages: | Japanese, English |
| Exam Duration: | 120 minutes |
| Related Certifications: | UiPath Certified Professional Agentic Automation Professional UiPath Agentic Automation Associate (UiPath-AAAv1) |
| Passing Score: | 70% |
| Sample Questions: | UiPath UiPath-AAPv1 Sample Questions |
| Exam Way: | Available at Pearson VUE test centers and through online proctored testing. The exam uses multiple-choice, drag-and-drop, and sequencing question formats. Exam duration is 120 minutes. The official exam description does not specify the total number of questions or domain weight percentages. |
| Pre Condition: | No mandatory prerequisite exam is specified in the official exam description. UiPath recommends familiarity with end-to-end automation workflow design, agent validation, guardrails, governance, and monitoring, as well as hands-on experience building and testing UiPath solutions. Passing UiPath Agentic Automation Associate is recommended for candidates seeking the next certification level but is not stated as a mandatory prerequisite. |
| Official Syllabus URL: | https://start.uipath.com/rs/995-XLT-886/images/UiPath%20Agentic%20Automation%20Professional%20Exam%20Description.pdf |
UiPath UiPath-AAPv1 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Conversational Agents | - Conversational Agents |
| Topic 2: Agentic AI and agentic automation concepts | - Definitions of agents and distinctions between generative AI and agentic AI - Agentic orchestration and collaboration between robots, agents, and humans - Best practices for agentic automation, including intelligent decision-making, adaptability, goal-oriented execution, and multi-task coordination |
| Topic 3: Coded Agents | - Coded Agents |
| Topic 4: UiPath Platform components and integrations | - Creating agent tools in Studio Web - Reusing existing agents within new agents - Troubleshooting tool execution using traces and evaluations - Designing input and output schemas for tools - Mapping connector actions into agent prompts - Creating connections through Integration Service - Integrating MCP assets as agent tools - Applying agent tool guardrails - Data Fabric integration - Using Run Job in Studio Web - Building and publishing API workflows as reusable agent tools |
| Topic 5: Agentic orchestration with UiPath Maestro | - Handling asynchronous agent completion events and callbacks - Configuring Service Tasks to invoke agents using Start and wait for agent - Defining global, local, and task-specific process variables - Using BPMN to model business processes and assign tasks to robots, agents, and humans - Configuring dynamic assignees, SLAs, and expiry rules for user tasks - Chaining multiple agents within a process - Capturing user inputs and returning structured data to processes - Configuring Service Tasks to invoke automation workflows from Orchestrator - Instance management - Defining and using API workflows - Using the expression editor and scripts for data transformation and conditional routing - Maestro best practices - Using Send and Receive tasks with Integration Service connectors and webhooks - Mapping input and output parameters between Maestro tasks and agents - Configuring User Tasks with Action Apps forms for escalations - Maestro control flow |
| Topic 6: UI Agent | - UI Agent (ScreenPlay) |
| Topic 7: Agentic discovery and blueprint design | - Defining agent goals and evaluation criteria - Differentiating system prompts and user prompts - Assessing agentic automation opportunities in business processes - Selecting tools appropriate to agent objectives - Designing agent stories using triggers, instructions, context, human-in-the-loop requirements, and tools - Mapping business process steps to agent tasks - Prioritizing automation opportunities based on feasibility and impact - Mapping context sources and grounding strategies |
| Topic 8: AI Trust Layer | - Using audit logs and usage summaries - Personally identifiable information masking in transit - Using a custom tenant as an LLM gateway |
| Topic 9: Agentic evaluations | - Selecting strict or flexible assertions based on use cases - Iteratively improving agent performance - Identifying edge cases and failure scenarios - Interpreting evaluation scores - Designing evaluation datasets that reflect real-world complexity - Analyzing evaluation failures to identify root causes and error patterns - Optimizing prompts using evaluation results - Differences between deterministic and model-graded evaluations - Executing evaluation sets and analyzing accuracy and reliability - Using execution traces to troubleshoot failed evaluations - Creating input-output pairs for diverse scenarios - Selecting deterministic and model-graded assertions - Evaluation concepts and their role in agent reliability |
| Topic 10: Autopilot for Everyone | - Using specialized Autopilots - Determining when to use Autopilot for Everyone |
| Topic 11: Prompt engineering | - Prompt engineering best practices - Crafting zero-shot prompts for simple tasks - Including context, instructions, output formats, and constraints - Designing structured few-shot prompts - Applying clarity, specificity, and conciseness - Iteratively refining prompts based on evaluation feedback |
| Topic 12: Agent management | - Analyzing execution traces to understand agent behavior - Best practices for building, publishing, and deploying agents - Using agent scores to track performance - Agent tool and context grounding simulations - Assigning policies at tenant, group, and user levels - Monitoring agent usage, unit consumption, and incidents - Applying governance policies to enable, disable, and control agent functionality |
| Topic 13: Escalations | - Human-in-the-loop concepts and the importance of human oversight - Configuring UiPath Action Apps for human-in-the-loop escalations - Defining escalation logic |
| Topic 14: Context Grounding | - Implementing index update strategies - Configuring thresholds and result limits for precision and relevance - Context grounding sources and configuration options - Monitoring index queries and jobs - Using context grounding indexes to store and retrieve relevant information for agent memory - Context grounding concepts and implementation - Context engineering best practices - Ingestion and retrieval methods |
UiPath Agentic Automation Professional Sample Questions:
Which approach follows best practices for implementing a multi-agent system?
- A. Focus on repetitive, rules-based automations where agents follow fixed, deterministic paths and do not require adaptive planning or coordination.
- B. Limit agent interaction to prevent complexity, assigning each agent a static function that never changes throughout the workflow lifecycle.
- C. Define all control logic and task order during the initial design phase, ensuring agents execute a predetermined set of actions without deviation, following fixed rules and deterministic paths.
- D. Design agents to collaborate and coordinate at runtime, using shared memory or communication layers to negotiate objectives, distribute tasks, and adapt dynamically to changing conditions.
Correct Answer: D 🗳️
Explanation: Only visible for Exam4Labs members. You can sign-up / login (it's free).
Which practice best helps you iteratively improve an agent's prompt quality through UiPath evaluations?
- A. Increase the model temperature to its maximum to force more creative outputs.
- B. Remove evaluations with lower scores to artificially raise the agent's average.
- C. Tune only the agent's evaluator thresholds without updating the prompt structure.
- D. Refine the prompt based on failed debug runs and add corrected outputs to the evaluation set.
Correct Answer: D 🗳️
Explanation: Only visible for Exam4Labs members. You can sign-up / login (it's free).
While designing a few-shot structured prompt for a customer support agent, you want the agent to handle refunds and send confirmation messages.
Which of the following is the best instruction for formatting the confirmation message?
- A. Send a formal response including general refund details without specifying the estimated refund time or enclosing the output within structured XML tags.
- B. Only mention the refund amount, excluding any other details or formatting in the response.
- C. Include order ID, refund amount, estimated refund time, and a polite message enclosed within tags.
- D. Provide the customer with a generic acknowledgment of the refund request without using any defined schema or structured output tags.
Correct Answer: C 🗳️
Explanation: Only visible for Exam4Labs members. You can sign-up / login (it's free).
In an agent run's trace view, what information does hovering over a node typically reveal?
- A. The agent's feedback score and retry count
- B. The agent's memory usage and model type
- C. The agent's role and prompt structure
- D. Execution status, timestamps, and input/output previews
Correct Answer: D 🗳️
Explanation: Only visible for Exam4Labs members. You can sign-up / login (it's free).
An agent needs to extract high-confidence data from structured documents and optionally permit human review before continuing.
Which tool configuration meets this need?
- A. Add a Web Search tool and filter results to validate extracted document fields.
- B. Add the Analyze Files tool and rely on token limits to determine when human validation is required.
- C. Add an IXP project as a tool and configure a Document Validation Task escalation for human validation of extracted data.
- D. Use DeepRAG with citations enabled to automatically correct low-confidence extracted values.
Correct Answer: C 🗳️
Explanation: Only visible for Exam4Labs members. You can sign-up / login (it's free).
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