Smarter Hand offs — Documentation & Transitioning to Development [5/6]

[5/6]
Smarter Hand offs — Documentation &
Transitioning to Development
Agentic Discovery Webinar
Series

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About UiPath Community Bengaluru!
We are a community of automation professionals and enthusiasts that acquire knowledge about the latest
in AI-powered automation and share it within the community.
You are welcome to enjoy the virtual and in-person experiences that our community has to offer:
- meet each other and share experiences from the automation industry
- find out about the latest developments in the UiPath Business Automation Platform
- get guidance and support through use cases, demos, and practical examples
https://community.uipath.com/bengaluru/

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Speaker
Pranav Kashyap
Team Lead-
Wonderbotz

4
Speaker
Akhil Padgilwar
Senior Software Engineer
qBotica

5
Speaker
Shradha Sarap
Senior Business Analyst-
Wonderbotz

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Speaker
Sushmita Dey
Senior Consultant- WonderBotz

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Documentation
approach variations
Practical
Illustration
Business–Tech
Handoffs
Data modeling for
adaptive
processes
BPMN for dynamic
agent flows
Agent design
documentation
template
Agenda for the day

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 Business Process
Model Notation
 Worldwide adopted
standard to model
business processes
and workflows
Understanding BPMN

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Events
Tasks
Level Of
Automation
Gateways
Pools and Lanes
Components of BPMN

DocumentationApproachVariations
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The "Black Box" Problem:
The Missing Memory Layer :
Traditional docs show steps, but not how agents actually decide
The Silent Failure Trap :
Challenges of Traditional Documentation in Agentic
Contexts
Traditional methods are insufficient for capturing the nuances of agentic systems, creating significant gaps
between design and implementation.
PDDs document workflows, not how agents learn/forget
Static docs assume perfect execution

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From Static to Dynamic: The Shift to Agentic
Documentation
This shift is crucial for bridging the gap between business needs and technical execution, demanding
a new approach to documentation.
Aspect Traditional Documentation Agentic Documentation
Focus Captures static process flows and technical
specs
Documents adaptive agent behaviors, goals,
and decision logic
Collaboration Business analysts hand over to technical teams;
limited ongoing alignment
Ensures continuous alignment across
business, engineers, and automation owners
Adaptability Often misses context-switches and dynamic
changes; updates are infrequent
Details agent prompts, context, and
adaptability for evolving needs
Lifecycle Integration Finalized early (at dev start), changes require
formal change management
Evolves continuously throughout automation
lifecycle, serving as a living blueprint

AgentDesignDocumentation(ADD)Template
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Agent Design Documentation is more than just a document-
• it's a living blueprint for your automation agent's success.
• It ensures everyone involved, from developers to stakeholders, shares a clear, unified
understanding of its purpose and function.
Defining the Agent
Purpose: Clearly states the agent's
role, goals, and the problem it solves.
Tasks: Details the specific functions
and actions the agent executes, step-
by-step.
Data Interaction: Explains how the
agent communicates with other
systems and data sources, including
inputs, outputs, and APIs.
The Power of Agent Design Documentation
Value to Your Team
Single Source of Truth: Eliminates
ambiguity and ensures everyone works from
the same understanding.
Minimizes Misinterpretation: Reduces
errors and rework by providing clear
guidelines.
Promotes Consistency: Ensures uniform
development practices and agent behavior
across its lifecycle.
The Outcome: A Seamless Development
Journey
Effective documentation leads to:
Reliable Development: Fewer bugs and more
predictable behavior.
Easier Maintenance: Streamlined updates and
troubleshooting.
Seamless Collaboration: Enhanced teamwork
across all technical teams and stakeholders.
Think of it as a GPS for your agent: it maps out the journey, identifies every turn, and ensures everyone
arrives at the same destination efficiently.

PracticalIllustration:BusinessRequirements
AnalysisWalkthrough
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Problem Statement
IT Service Management (ITSM) teams are inundated with repetitive, time-consuming
requests that strain resources and impact service quality. The key challenges include-
Repetitive Request Types:
• Application access provisioning
• Password resets
• MFA (Multi-Factor Authentication) resets
Consequences:
• Delays in Resolution: Manual processing slows down response times.
• Increased Error Rates: Human errors lead to incorrect actions or misrouting.
• High Support Costs: Manual handling consumes significant resources and
escalates operational expenses.
Use Case
RPA Vs Agentic

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Need for Agentic Automation
Businesses require intelligent agent that can:
 Interpret requests dynamically
 Handle missing or unclear details with adaptive logic
 Error Reduction through Guardrails
 Cost Efficiency & Service Quality Gains

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With a Checklist
• Forces clarity: asks the right
questions upfront.
• Captures both steps AND
intelligence (goals, edge cases,
context).
• Ensures shared understanding,
leading to predictable agent
responses.
Checklist Magic: Turning Chaos into Clarity
Without a Checklist
• Incomplete requirements lead to
unclear agent behavior.
• Assumptions cause costly rework
and missed scenarios.
• Developers guess intent, not build
to it.

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Agentic Automation Flow: From Rules to Reasoning

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Time for our ADD walkthrough! 🚀 Let’s see how
goals, prompts, edge cases, and adaptive logic
come together—turning business intent into smooth
technical execution.
ADD Walkthrough: Integrating for Intelligent Agent
Behaviour

DataModelingforAdaptiveProcesses
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Data Modeling for Adaptive Processes
Healthcare
Diagnostics
Patient records use an evolving schema;
as new symptoms appear, the model
adapts by adding new metrics, allowing
medical staff to capture richer and more
relevant information without redesigning
the whole system.
Fraud Detection
Adaptive models constantly learn from
new transaction patterns, instantly
updating to spot previously unknown
fraud types—fields and thresholds may
be added as fraud schemes evolve

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Techniques for Adaptive Processes
Entity-Relationship + Metadata
Extensions
• Still define entities (Invoice, Purchase Order, Supplier).
• But add metadata schemas (JSON/YAML) for things
like:
• Prompt templates
• Confidence thresholds
• Context variables
Example:
{
"entity": "Invoice", "attributes":
["InvoiceID", "Vendor",
"Amount", "DueDate"], "context":
{"confidence": 0.92, "source":
"OCR"}, "decision_rules": ["If
AmountMismatch > 5%,
escalate"]
}

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Graph Data Models
• Represent adaptive flows as graphs (nodes = states,
edges = transitions).
• Useful when agent decisions depend on multi-hop
relationships.
• Example: Vendor → Past Deliveries → Payment
Performance → Approval Path.
Event-Driven Data Models
• Each process step = event with attributes.
• Process state = accumulation of events (like Event
Sourcing).
• Example:
• Event: InvoiceUploaded → State: Pending
Validation.
• Event: Validation Failed → State: Escalated.
Techniques for Adaptive Processes

BestPracticesforBusiness-to-TechHandovers
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Ensuring Seamless Business-to-Tech Handovers
Clarity is
King
Show, Don’t
Just Tell
Bring It to
Life
Close the
Gaps
Consistency
Matters

Smarter Hand offs — Documentation & Transitioning to Development [5/6]

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