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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Governance, Evaluation & Trust | 15% | - Agent performance evaluation - Guardrails and responsible AI - Observability and reliability |
| Topic 2: Agentic Automation Fundamentals | 20% | - Agents vs traditional robots - Core principles of agentic automation - AI, LLM and generative AI concepts |
| Topic 3: Orchestration & Human-in-the-Loop | 20% | - Escalations and Action Center - Service tasks and agent invocation - UiPath Maestro and BPMN modeling |
| Topic 4: Agent Design & Development | 25% | - Agent Builder in Studio Web - Prompt engineering best practices - Tools, connections and integration services |
| Topic 5: Context & Knowledge Management | 20% | - Data sources and retrieval methods - Context packages and grounding - Knowledge base integration |
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NEW QUESTION # 60
When mapping business process steps to agent tasks using Task Capture, which BPMN element is mapped as a 'Decision' rather than as a unique element?
Answer: D
Explanation:
Dis correct - inTask CaptureandBPMN modeling, theExclusive Gatewayis the BPMN element that represents adecision point. It is used to:
* Split the process intomutually exclusive paths
* Route flow based on acondition or choice
When mapping these processes toagent behavior, the Exclusive Gateway typically translates to a"Decision" node, where the agent:
* Evaluates logic (e.g., "Is amount > $10,000?")
* Selects one path forward (e.g., "Escalate" vs. "Auto-approve")
This is a fundamental construct in UiPath'sagentic process modeling, enabling agents to handlebranching logic, make contextual choices, or call different tools based on runtime data.
Option A (Task) represents an activity, not a decision.
B (Swimlane) is used to group actions by role - not functional logic.
C (User Task) represents human involvement - not branching conditions.
UiPath emphasizes decision modeling to make agentsadaptive and responsive, and Exclusive Gateways are the tool to model such decisions cleanly and visually.
NEW QUESTION # 61
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?
Answer: C
Explanation:
This is a repeat of Question 16, and the correct answer remains A.
Even when few-shot examples are included, omitting clear formatting instructions leads to inconsistent outputs, which can break downstream processes in agentic automation.
UiPath's Prompt Engineering guidance emphasizes that instruction clarity is as important as examples - especially when output format matters (like agendas, classifications, or structured text).
An optimal prompt includes:
A task description (e.g., "Convert meeting notes into a 3-section agenda") Clear format instructions (e.g., use bullet points, bold headers) Few-shot examples Optional constraints like length or tone Without that first element - clear instructions - the LLM has to guess the output format, leading to variance and unreliability.
NEW QUESTION # 62
When exploring agentic automation discovery, which dimension ensures the solution aligns with the responsibilities and challenges of the individuals involved?
Answer: C
Explanation:
Cis the correct answer - apersona-centered approachis a cornerstone of UiPath'sAgentic Discovery and Blueprint Designmethodology.
When identifying automation opportunities, UiPath stresses:
* Understanding the actual people behind the process
* Mapping theirpain points,repetitive tasks,decision fatigue, andworkflow bottlenecks
* Designing agents thatserve that roleand embed naturally into their day-to-day responsibilities This ensures agents are:
* Valuable(they solve the right problems)
* Adoptable(they fit into how people actually work)
* Sustainable(they evolve with user needs)
Options A, B, and D areanti-patterns- each represents a discovery flaw where automation is misaligned due toignoring human context.
Persona definition is essential for designing agents thatact as reliable digital coworkers, not just process bots.
NEW QUESTION # 63
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?
Answer: A
Explanation:
Bis correct - when a field (likeChannel Id) is set toPrompt, the agent will attempt to infer its valueat runtime, based on theinstructions in the promptand the context provided.
This is the default and preferred mode for agent tools when:
* The agent has enough context or memory to decide
* You wantLLM autonomyin filling the field dynamically
* You're using prompt instructions like: "Post to the user's default Slack channel" Option A is incorrect - "Argument" is used when you're passing aspecific variableinto the agent prompt (not inferred).
C misunderstands data flow direction - "Output" is not relevant for input fields.
D is invalid - "Variable" is not the standard method for field inference in this scenario.
This aligns with UiPath'sagent + tools orchestrationmodel usingStudio Web's low-code agent builder.
NEW QUESTION # 64
Which similarity search function is leveraged when Context Grounding is used by UiPath Products like Agents?
Answer: C
NEW QUESTION # 65
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