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| Section | Objectives |
|---|---|
| Prompt Engineering for Agents | - Zero-shot and few-shot prompting - System prompts and constraints |
| Autopilot for Everyone | - AI-assisted automation building - Use cases and capabilities |
| Agentic AI Fundamentals | - AI agents vs rule-based automation - Agentic automation concepts |
| Escalations & Human-in-the-Loop | - Action Center workflows - Exception handling and escalation patterns |
| Agent Blueprint Design | - Agent architecture design - Workflow decomposition |
| Context Grounding (RAG) | - Data grounding strategies - Retrieval-Augmented Generation concepts |
| Agent Discovery & Process Assessment | - Identifying automation opportunities - Process suitability for agentic automation |
| UiPath Platform Components | - Agent Builder and Orchestrator basics - Studio Web and Autopilot |
| Agentic Evaluations & Governance | - Guardrails and validation logic - LLM-as-a-judge metrics |
| Agentic Orchestration (Maestro) | - Workflow orchestration with agents - BPMN-based process design |
1. Why is an agent story important in the development life-cycle?
A) An unclear agent story helps SMEs and stakeholders understand the potential risks associated with the agent
B) A good agent story helps the developers who will build the agent to focus on the essential features that deliver value
C) A detailed agent story is only necessary when showcasing the agent's functionality to key stakeholders, rather than guiding the development process
D) A poorly defined agent story enables developers to identify improvement opportunities
2. For what primary reason should you supply a description for every input and output argument in an agent?
A) Argument descriptions are required only for input arguments; output arguments are inherently self- explanatory and do not benefit from them.
B) Adding descriptions forces Studio Web to treat all arguments as mandatory fields that block deployment if left empty.
C) Clear descriptions help the agent understand how to use each argument effectively while generating or returning results.
D) Descriptions cause Orchestrator triggers to pre-populate the arguments automatically, eliminating manual mapping.
3. Four draft system prompts are shown for an invoice-approval agent. Based on UiPath guidance for context, instruments, and output format constraints, which draft is the most robust choice?
A) You are an invoice approver. After processing, output exactly the following JSON template:
{ "id": "ABC-123", "status": "approved", "amount": 9999.9 }
Extract {{invoice_ID}} from the email text.
When an {{invoice_ID}} is found, run the LookupInvoice tool to retrieve invoice amount and supplier name.
If the total # $10,000, escalate the case to Finance in Action Center, sending {{invoice_ID}}, amount, and supplier.
If the total > $10,000, approve the invoice.
Populate the fields above with real data.
B) You are an invoice-approval agent who deals only with supplier invoices and rejects any other request.
Extract {{invoice_ID}} from the email text.
When an {{invoice_ID}} is found, run the LookupInvoice tool to retrieve invoice amount and supplier name.
If the total # $10,000, escalate the case to Finance in Action Center, sending {{invoice_ID}}, amount, and supplier.
If the total > $10,000, approve the invoice.
Return a reply wrapped inside invoice_status: tags: use <approved> or <awaiting_review> as appropriate.
Follow a concise, professional tone and refuse tasks outside invoice approval.
C) You are an invoice approver. After processing, output exactly the following JSON template:
{ "id": "ABC-123", "status": "approved", "amount": 9999.9 }
Extract the {{invoice_ID}} from the email text.
Use LookupInvoice to get the invoice amount and supplier name.
Escalate to Finance if amount # $10,000.
If amount > $10,000, approve the invoice.
Populate the fields above with real data.
D) You are an invoice-approval agent who deals only with supplier invoices and rejects any other request.
Extract invoice_ID from the email text.
When an invoice_ID is found, run the LookupInvoice tool to retrieve invoice amount and supplier name.
If the total # $10,000, escalate the case to Finance in Action Center, sending invoice_ID, amount, and supplier.
If the total > $10,000, approve the invoice.
Return a reply wrapped inside invoice_status: tags: use <approved> or <awaiting_review> as appropriate.
Follow a concise, professional tone and refuse tasks outside invoice approval.
4. 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?
A) Providing only examples without additional context about the task.
B) Adding clear instructions detailing the output format.
C) Adding randomized formatting examples to test the agent's creativity.
D) Including constraints to limit the length of the agenda for simplicity.
5. What is the primary role of guardrails in tools?
A) Guardrails are used exclusively to automate all tool corrections without the possibility of triggering human intervention.
B) Guardrails only validate tool inputs during development and do not address unpredictable behaviors at runtime.
C) Guardrails are designed to apply only after tool execution, without influencing pre-execution conditions.
D) Guardrails control unexpected behaviors within tool calls deterministically, allowing developers to configure conditions for human intervention and escalations.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: B | Question # 5 Answer: D |
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