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| Section | Weight | Objectives |
|---|---|---|
| Agent Design & Development | 25% | - Prompt engineering best practices - Agent Builder in Studio Web - Tools, connections and integration services |
| Agentic Automation Fundamentals | 20% | - Agents vs traditional robots - Core principles of agentic automation - AI, LLM and generative AI concepts |
| Context & Knowledge Management | 20% | - Data sources and retrieval methods - Knowledge base integration - Context packages and grounding |
| Orchestration & Human-in-the-Loop | 20% | - Escalations and Action Center - UiPath Maestro and BPMN modeling - Service tasks and agent invocation |
| Governance, Evaluation & Trust | 15% | - Observability and reliability - Guardrails and responsible AI - Agent performance evaluation |
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NEW QUESTION # 49
An agent is being designed to generate step-by-step troubleshooting guides for software issues. Testing shows that the guides lack clarity and include redundant steps, confusing users. What is the best refinement for the prompt?
Answer: A
Explanation:
Cis correct - the best refinement is toexplicitly instruct the agent to produce actionable, concise, and non-redundant steps. UiPath emphasizes that LLM outputs improve significantly when the prompt includes clear task goals + structure + tone guidelines.
In this case:
* "Avoid repeating steps"
* "Make each step actionable"
* "Keep it short and clear"
...are examples ofinstructions that directly reduce confusion and redundancyin generated content.
Options A and B introduce vagueness or verbosity, which worsen the problem.
D removes detail - the opposite of what's needed forstep-by-step clarity.
UiPath's Prompt Engineering Toolkit recommendstight formatting, tone, and output constraintsfor high- quality, consistent automation guides.
NEW QUESTION # 50
A company launches a marketing campaign powered by generative AI and agentic AI technologies. What best describes how their roles differ?
Answer: D
Explanation:
The correct answer isA- UiPath clearly differentiatesGenerative AIfromAgentic AIbased on function and scope:
* Generative AIfocuses oncontent creation: generating emails, blog posts, social posts, or product descriptions using LLMs.
* Agentic AIwraps this output withcontextual automation- it interprets, makes decisions, triggers actions, and interacts across systems.
In this marketing scenario:
* Generative AI might write an email campaign or social caption.
* Agentic AI would decidewhento send it, towhom, and based onwhich signals or workflows- possibly also adjusting the content based on campaign performance, customer segments, or behavior.
UiPath's Agentic Automation model positions agentic AI as the"doer"- an orchestrator of dynamic workflows, not just a content engine. That's why it underpins use cases like intelligent triage, escalation, or campaign coordination.
Options B, C, and D conflate or reverse these roles, which don't align with UiPath's design guidance.
NEW QUESTION # 51
You want your agent to call an existing UiPath process by adding it in the Tools # Processes. Which prerequisite must be met before the process becomes selectable?
Answer: A
Explanation:
Bis the correct answer - in UiPath'sAgent Builder (Studio Web), when you want to invoke an existing UiPath process from an agent (viaTools # Processes), that process must meettwo key prerequisites:
* It must be published and deployed to a shared Orchestrator folder
* You - and the agent - must have access to that folder
This ensures that:
* The agent canlocate and run the processat execution time
* Role-based access control (RBAC) is respected
* Input/output arguments, execution logs, and exceptions are properly managed within the correct environment This aligns with UiPath'sOrchestrator-integrated agent orchestration model, where security and deployment visibility are tightly governed. It also allows agent authors toreuse existing RPA logicinside dynamic agent flows without duplicating automation work.
Option A and D incorrectly imply that argument types affect process visibility - that's false. Agents can invoke processes withany argument signature, as long as mapping is defined.
Option C is incorrect - publishing alone is not enough.Deployment and permissionsare required for the process to appear in the tool selector.
This model ensures that agents can call any compliant UiPath processsecurely, reliably, and in line with enterprise governance.
NEW QUESTION # 52
Which statement best describes UiPath Maestro's capability for deploying AI agents within a BPMN-modeled process?
Answer: A
Explanation:
The correct answer isC- UiPathMaestroenablesagentic orchestrationby serving as aprocess modeling and execution layerfor AI agents, RPA bots, human reviewers, and external systems. It supports BPMN-based modeling and integrates bothUiPath-built agentsandexternal agents, such as those fromLangChain,CrewAI
, orAgentforce.
Maestro provides aconsistent frameworkthat allows:
* InvokingLLM-powered agentsas subprocesses or service calls
* Managingescalations and human-in-the-loop workflows
* Defining structuredinputs, outputs, and triggersusing visual tools
* Coordinating acrosshybrid environments, mixing RPA, agents, and APIs
This aligns with UiPath'sAgentic Automation vision, where agents are not isolated but operate within enterprise-grade governance and control structures. Maestro enables scalable deployment ofgoal-driven, adaptive agentsinside complex, orchestrated processes.
Option A is incorrect - Maestro doesn't embed code scripts or rely solely on external runtimes.
B is false - Maestro is broader than just Agentic and Integration tasks.
D is outdated - Maestro can orchestrate third-party agents with human review checkpoints via its own framework.
Maestro essentially acts as thecentral nervous systemfor agent coordination, making C the most accurate answer.
NEW QUESTION # 53
A business is looking to automate its workflows and has both structured, repetitive tasks (like data entry) and unstructured, exception-heavy processes (such as responding to diverse customer queries). How should they combine agents and robots (RPA) to achieve optimal automation results?
Answer: C
Explanation:
Ais the correct andUiPath-recommended approach:
* RPA botsare ideal forstructured, rule-based, high-volume tasks- like data entry, file manipulation, system integration - wherepredictability and speedare key.
* Agentic AIexcels inunstructured, human-like decision scenarios - likeinterpreting emails,triaging support requests, orresponding to exceptionsusing LLMs and contextual memory.
UiPath promotes ahybrid automation model:
* Letrobotshandle deterministic workflows.
* Letagentsmanage ambiguity, natural language, and decision-making.
* Lethumanshandle escalations or approvals when required.
This createsscalable, intelligent, and efficientworkflows that combine strengths from both systems.
B and C are incorrect because neither agents nor bots alone are sufficient across all use cases.
D reverses the design logic - agents arenotbest for structured tasks; RPA is.
This hybrid approach is foundational in UiPath'sAgentic Orchestration and Co-Pilotstrategies, ensuring right-tool-for-the-taskautomation at scale.
NEW QUESTION # 54
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