UiPath UiPath-AAAv1 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Governance, Evaluation & Trust | 15% | - Guardrails and responsible AI - Agent performance evaluation - Observability and reliability |
| Topic 2: Agentic Automation Fundamentals | 20% | - Core principles of agentic automation - AI, LLM and generative AI concepts - Agents vs traditional robots |
| Topic 3: Context & Knowledge Management | 20% | - Knowledge base integration - Context packages and grounding - Data sources and retrieval methods |
| Topic 4: Orchestration & Human-in-the-Loop | 20% | - Escalations and Action Center - UiPath Maestro and BPMN modeling - Service tasks and agent invocation |
| Topic 5: Agent Design & Development | 25% | - Agent Builder in Studio Web - Tools, connections and integration services - Prompt engineering best practices |
UiPath Certified Professional Agentic Automation Associate (UiAAA) Sample Questions:
1. How does adjusting the "Number of results" setting affect the agent's use of context from indexes?
A) It makes the agent ignore all context completely, resulting in outputs that are entirely disconnected from the indexed data, regardless of its relevance to the query or prompt provided.
B) It modifies the similarity threshold for chunk retrieval and lowers the number of tokens used.
C) It changes the number of chunks returned, impacting both the size of the grounding payload and the filtering of relevant information.
D) It selects which Orchestrator folder to use, determining the location of stored workflows and deciding which set of predefined rules will apply during data retrieval and processing.
2. A team is building an AI agent that drafts personalized marketing emails. The quality of the drafts depends on tone, alignment with brand voice, and personalization. What evaluation approach is best?
A) Evaluation using a character count threshold to assess message quality.
B) Random sampling with A/B testing.
C) Deterministic evaluation using a checklist of key phrases.
D) Model-graded evaluation to capture nuanced style and relevance.
3. You are building an agent that classifies incoming emails into one of three categories: Urgent, Normal, or Spam. You want to improve accuracy by using few-shot examples in a structured format. Which approach best supports this goal?
A) Show one example and leave the label blank for inference.
B) Use examples such as:
Input: "Please address this issue immediately, server is down!" Output: "Urgent"
C) Include three random emails and let the LLM guess the intent.
D) Use unlabeled prompts followed by ranked categories:
Classify this. "Need update on report." - [1] Urgent [2] Normal [3] Spam
4. 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-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.
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 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.
5. When exploring agentic automation discovery, which dimension ensures the solution aligns with the responsibilities and challenges of the individuals involved?
A) Defining the role or persona by considering the people performing the tasks and their needs, challenges, and responsibilities.
B) Mapping systems, applications, and tools without understanding how they interact with human roles.
C) Focusing solely on task dependencies while neglecting the daily pain points of individuals executing these tasks.
D) Assessing structured and unstructured knowledge contexts required for the tasks but excluding the personas performing these operations.
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: A |














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