From Bots to Brains: Getting Started with Agentic Automation in UiPath

Step beyond traditional robotic process automation (RPA) and explore the future of intelligent automation with UiPath Agentic Automation. This one-hour session will introduce you to the transformative world where autonomous AI-powered agents collaborate with robots and humans to deliver smarter, more adaptive automation outcomes.

Join us to learn the foundational concepts of agentic automation, understand how UiPath’s Agent Builder and orchestration platform empower these intelligent agents, and see a live demo of building your first agent in action. Whether you’re new to UiPath or looking to expand your automation toolkit, this session provides practical insights and best practices to get started.

In this Session:

✅ Gain a structured introduction to agentic automation concepts and the UiPath ecosystem
✅ Understand the key differences between traditional RPA bots and intelligent agents
✅ Explore real-world use cases and the architecture of agentic automation
✅ Witness a live demo building your first agent and learn best practices for success

Speaker:
Srinivas Kadamati, UiPath MVP, Sr. Tech Lead @Proservartner

1. From Bots to Brains
Getting Started with Agentic Automation with UiPath
Speaker : Srinivas K

2. Agenda
Journey Towards Agentic AI
High-level view of how Agentic AI works
Characteristics of Agentic AI
Guidelines for Effective UiPath Agent
Effective Prompt Engineering
Context Grounding
Use case Explanation
Demo

3. WHO AM I
SRINIVAS K(Srini)
SeniorTechLead @ Proservartner
1.UiPath MVP (Most Valuable Professional) 2022-2025
2.HyperHackTeam member and Team secure 2
nd
Place.
3.??????�??????????????????�????????????�????????????????????????????????????��Team member and Team secure
Runner-up Prize.

4. From Bots to Brains
Journey towards Agentic AI
from rule-following bots to intelligent agents capable of independent action.

5. How DoesAgenticAI work
How the bot Think

6. How DoesAgenticAI work
How the bot Think
Autonomous
The most important advancement of agentic systems is that they allow
for autonomy to perform tasks without constant human oversight.
Proactive
Agentic systems provide the flexibility of LLMs, which can generate
responses or actions based on nuanced, context-dependent understanding,
with the structured, deterministic and reliable features of traditional
programming.
Specialized
Agents can specialisein specific tasks. Some agents are simple, performing
a single repetitive task reliably. Others can use perception and draw on
memory to solve more complex problems.
Adaptable
Agents can learn from their experiences, take in feedback and adjust their
behaviour. With the properguardrails, agentic systems can improve
continuously.
Intuitive
Because LLMspoweragenticsystems, users can engage with them with natural
language prompts. This means that entire software interfaces—think of the many
tabs, dropdowns, charts, sliders, pop-ups and other UI elements involved in the
SaaS platform of one’s choice—can be replaced by simple language or voice
commands.

7. Guidelines for Effective UiPath Agent
Guardrails
• Built-in safety checks & control tools
• Trigger actions: Log, Block, Filter
• Compliance path enforcement
• Clear escalation proceduressyste
Effective Prompt Writing
• Use clear, structured prompts to guide AI behavior
• Prefer few-shot or few-chain-of-thought prompting
• Write thoughtful, outcome-focused prompts
• Define expected format, tone, and style
Context Grounding
• Provide agent-specific knowledge and parameters
• Importance: Ensures accurate reasoning and reliable execution
Escalations
• Enable human-in-the-loop handoff for critical decisions
• Review sensitive agent actions (e.g., JSON/XML operations)
• Pro Tip: Validate outputs for accurate agent execution
• Example: Triggered issues → realistic, explainable outcomes

8. Effective Prompt Engineering
Zero-Shot Prompt
• Asking the model to perform a task without
providing any examples
•The model relies purely on its pre-trained
knowledge to understand and answer
•Examples:
•Summarize this document in one paragraph.
•List three benefits of using RPA in financial
services.
Few-Shot Prompt
• Providing a few examples of Input-Output pairs
•The model learns the pattern or Style from the
given examples
•Examples:
•Input: "Hello" → Output: "Hi there! How can I
assist you today?“
•Input: "Write a formal thank-you note for a
client meeting."
Output: "Dear [Client], thank you for your
valuable time today. We appreciate your
insights and look forward to our collaboration."
Chain-of-Thought Prompt
• Encourage the model to show intermediate
reasoning steps before giving the final answer
•You instruct the model to think “Step by Step”
•Examples:
•"Provide the final decision and a short risk
assessment (3 bullets). Then add a 3-step
rationale summarizing how the risks and
benefits were compared to arrive at the
decision. Scenario: <insert scenario>.“
•Answer the question concisely. Then provide a
numbered summary (3–5 short steps) showing
the key reasoning used to reach that answer.
Question: <insert question>."

9. CONTEXT GROUNDING
Context Grounding is a
component of the UiPath AI Trust
Layer which allows you to bring in
your data to generate more
accurate, reliable GenAI
predictions.
•Ingestion: Convert business data into
representative embeddings using UiPath-
managed embedding models.
•Embedding: A representation of business data
that an LLM can understand and search
through.
•Search through LLM-ready business data to
find the most relevant information. Context
Grounding uses a variety of extraction,
chunking, retrieval, and re-ranking
techniques that are optimisedbased on
different data formats and queries.
•Ground and update prompts with
the most relevant information from
the semantic similarity search
results, then execute a generation
via an LLM hosted through the LLM
Gateway of the AI Trust Layer.

10. Manual Typical Accounts Payable Process
Heavily manual processes that is reliant on Humans to perform all the steps

11. Automation &AI evolution for Accounts Payable
Automation & Intelligent Automation with UiPath(Act One)

12. Automation &AI evolution for Accounts Payable
Agentic Automation with UiPath(Act Two)

13. UseCases–When to Use Agent / Workflow
Help Desk Automation
Sales email generation
Invoice Processing
Employee Onboarding
Agent
Agent
Depends, Agent / RPA Workflow
RPA Workflow

14. DEMO