UiPath Certified Professional Agentic Automation Builder Professional Preparation Details
Preparing for the UiPath-AABPv1 UiPath Certified Professional Agentic Automation Builder Professional exam? This study guide maps all seven exam domains to official UiPath documentation for every objective. You can also explore more UiPath certification study guides on the UiPath category to keep building your skills.
UiPath Certified Professional Agentic Automation Builder Professional Materials
1.0 Agentic Business Orchestration Foundations
Describe what business process automation is and the value it brings.
Differentiate pure automation from agentic business orchestration.
Choosing between Maestro Orchestrate and Maestro Automate
Define ML, LLMs, and generative AI, and differentiate generative AI from agentic AI.
Agent capabilities in the UiPath Platform™
Differentiate agents from robots and explain when each is appropriate.
Best practices for building agents
RPA worfklows vs. API workflows
Interpret Process Definition Documents (PDD), Solution Design Documents (SDD), and Agent Design Documents (ADD).
UiPath automation implementation methodology fundamentals
Best practices for building agents
Describe the project implementation stages based on the UiPath Implementation Methodology.
UiPath automation implementation methodology fundamentals
2.0 UiPath Platform
Describe the project types in Studio Web and choose the right one for a given business problem.
RPA workflow, API workflow, agent, app, agentic process, and case management projects
Designing RPA workflow projects
Match a project type to the characteristics of a business problem
RPA worfklows vs. API workflows
Maestro BPMN vs. Maestro Case: when to use case management
Choosing between Maestro Orchestrate and Maestro Automate
Explain licensing basics at the awareness level: Agent Units, AI Units, and Robot Units.
Unified Pricing: Licensing plan framework
Flex: Licensing plan framework
3.0 Deterministic Automation
Explain the difference between attended, unattended, and serverless processes.
Automation Cloud Robots – Serverless
Use variables, arguments, and control flow (sequences, if, loops, switch) in a workflow.
Manipulate basic data: strings, numbers, dates, lists, and DataTables.
Managing the data in a project
Passing values between activities
Explain how UI Automation works in the modern design experience.
Modern UI Automation activities and methods
Differences Between Modern Experience and Classic Experience
Using UI Automation for browser interactions
Input and output methods, and the trade-offs between them
Targeting, selectors, and descriptors in the modern experience
Reusing objects and UI libraries
Healing Agent and Unified Target
Describe ScreenPlay and the use of Semantic Activities in UI Automation.
ScreenPlay as runtime, LLM-based UI navigation
Running and inspecting the execution results
When to apply semantic activities instead of classic targeting
ScreenPlay feature availability
Healing Agent and Unified Target
Differences Between Modern Experience and Classic Experience
Apply an introduction to REST APIs and JSON data handling.
Building your first API workflow
Use Integration Service connectors and triggers, and create end-to-end API workflows.
Configure connections, connectors, and event triggers in Integration Service
Organizing and sharing connections
Build and publish an end-to-end API workflow
Building your first API workflow
Use App projects and route work to humans via Action Center.
Pages, forms, controls, and inline automation in App projects
Human-in-the-loop (HITL) routing and action handling in Action Center
Adding an action app to an automation
Designing long-running workflows
Apply reliability practices: debugging, exception handling, and logging.
Debug modes, breakpoints, and the panels used to inspect runtime state
Exception handling patterns and recovery behavior
Log interpretation and logging best practices
Protecting Sensitive Information
4.0 Agentic Orchestration and Specialized AI
Apply BPMN for process orchestration.
Design BPMN orchestrations for long-running processes
Understanding Maestro BPMN modeling
Implementing a complex BPMN process
Differentiate UiPath Maestro orchestration from REFramework and queue-based patterns
Manage state, callbacks, and asynchronous execution.
Define global, local, and task-specific variables for process data
Variables and Expression editor
Configuring properties and data
Understanding Maestro BPMN implementation
Variables and element filtering (BPMN)
Map input and output parameters between Maestro tasks and agents
Configuring properties and data
Variables and Expression editor
Handle asynchronous agent completion events and callbacks
Coordinate multiple actors: agents, automations, humans, and APIs.
Use service tasks and send/receive tasks to call connectors and webhooks
About the HTTP Webhook connector
Chain multiple agents within a single orchestration
Understanding Maestro BPMN implementation
Capture user input through Action Apps forms and apply SLAs
Adding an action app to an automation
Setting SLAs and automated escalation rules
Apply case management orchestration.
Model stateful, long-running cases with dynamic task addition and parallel branches
Maestro BPMN vs. Maestro Case: when to use case management
Modeling primary and secondary stages
Build your first case with Maestro Case
Maestro Case component dictionary
Design escalation paths and SLAs
Setting SLAs and automated escalation rules
Exit rules and early stage termination
Configuring a rework loop (re-entry)
Implementing stage-level personas and permissions
Coordinate case-management orchestration with automations and agents
Establishing task I/O and write-back contracts
Configuring and testing the Case Manager Agent (preview)
Case Manager input and output contract
The Maestro Case lifecycle: from event trigger to app experience
Apply reliability, instance management, and recovery in orchestrated processes.
Manage, pause, resume, and recover process instances
Working with instance management
Managing live case instances: pause, migrate, and retry
Apply process optimization techniques and UiPath Maestro best practices
Common implementation scenarios
Describe specialized AI fundamentals: Document Understanding, Communications Mining, AI Center, and AI Trust Layer.
Introduction to UiPath Communications Mining
Define what UiPath Document Understanding is and distinguish structured, semi-structured, and unstructured documents.
Describe AI Trust Layer concepts: PII masking, LLM gateway, and audit and usage summary.
Managing AI Trust Layer policies
5.0 UiPath for Coding Agents
Explain AI-assisted authoring concepts.
What UiPath for Coding Agents is, and which coding agents are supported
Where to run your coding agent
The value of skills, enterprise execution, and platform convergence
How automations created by a third-party coding agent are governed once they run in production
Use the uip CLI and the skills library.
Installation, authentication, and everyday usage of the uip CLI
Authenticating in interactive and non-interactive (pipeline) contexts
Deploy to Orchestrator from CI
Installing skills globally or per project from the skills catalog
Describe AGENTS.md and how it is used
Give your agent project context
Reviewing and validating output
Generate, review, and correct workflows with a coding agent.
Use the Studio terminal panel to run a coding-agent session
Where to run your coding agent
Review AI-generated workflows and interpret Workflow Analyzer rule findings
Reviewing and validating output
Debug an AI-generated workflow and validate it before publishing
About Publishing Automation Projects
Describe the usage of Delegate, the Healing Agent, and the Diagnose Agent, and govern AI-assisted development.
Autopilot for Everyone and Specialized Autopilot: what is surfaced to users and why
Managing Autopilot for Everyone
Autopilot for Agents (Preview)
Healing Agent behavior and its limits in unattended execution
Healing Agent and Unified Target
Operationalize AI-assisted development safety
Reviewing and validating output
Enabling Healing Agent using the AI Trust Layer policy
Apply governance to coding-agent usage in enterprise repositories
Give your agent project context
Managing AI Trust Layer policies
6.0 Agents and Operational AI
Apply agent design and architecture principles.
Translate a business process into an agent task
Best practices for building agents
Building an agent in Studio Web
Define agent goals and evaluations
Best practices for building agents
Apply prompt hierarchy, context sources, and grounding strategies
Best practices for context engineering
Optimize cost management and token limitation
Choosing the best model for your agent
Settings for Studio Web Policies
Best practices for context engineering
Apply prompt engineering for production.
Zero-shot prompts and few-shot prompts with context
Best practices for building agents
Best practices for context engineering
Structure instructions, output format, and constraints
Prompt engineering best practices
Best practices for building agents
Best practices for context engineering
Best practices for publishing and deploying agents
Configure context grounding and agent memory.
Context grounding sources, thresholds, and ingestion methods
Working with Context Grounding
Short-term agent memory
Managing memory spaces (Preview)
Best practices for context engineering
Index update strategy and monitoring
Managing Context Grounding indexes
Governing contextual data for GenAI features
Best practices for DeepRAG and Batch Transform: JIT vs. index-based strategies
Build and use tools, connectors, MCP, and agents-as-tools.
Create, build, and publish tools in Studio Web
Building effective agent tools
Configuring simulations for agent tools
Publishing and deploying the agent
Integrate MCP assets within an agent
Use Integration Service connectors and API workflows as reusable agent tools
Building your first API workflow
Build agents as code.
Build, debug, and deploy Python agents using LangChain and LangSmith
Building and deploying coded agents
Build coded agents with Coding Agents
Package and publish an agent as a deployable artifact in a Solution
Publishing and deploying solutions
Clone a low-code agent as coded
Apply versioning and lifecycle management to agents
Describe specialized agent types.
Conversational Agents and ScreenPlay
Operationalize agents inside orchestrated processes alongside robots and humans
Apply operational AI practices: escalation, safety, and observability.
Design escalation paths for agent decisions
Setting SLAs and automated escalation rules
Best practices for building, publishing, and deploying agents
Best practices for building agents
Best practices for publishing and deploying agents
Publishing and deploying the agent
7.0 Evaluations, Governance and Reliability
Apply evaluation concepts and build evaluation datasets.
Produce repeatable evidence that a revised prompt or tool-selection change is safe to promote
Configuring simulations for agent tools
Define evaluation criteria for agent output fields, including Boolean, numeric, and controlled-string types
Apply groundedness checks so claims remain supported by retrieved content across a full run
Scope an evaluation set to an agent’s arguments, input fields, and consumers
Managing runtime evaluations (Preview)
Define assertions and analyze evaluation results.
Assert on the first-level output fields of standalone agents in Agent Builder
Building an agent in Studio Web
Interpret the default output.content field written by an inline agent node in a Maestro flow
Validate a returned root JSON object against a release gate
Settings for Studio Web Policies
Best practices for publishing and deploying agents
Analyze Tools and Escalations behavior surfaced in an evaluation run
Managing runtime evaluations (Preview)
Apply governance controls to agent building and execution.
Configure entitlements that permit or prevent a tenant’s users from building or running agents
Managing AI Trust Layer policies
Settings for Studio Web Policies
Apply out-of-the-box guardrails and describe runtime behavior when the entitlement is disabled
Select guardrail action types appropriate for business-critical data
Resolve policy precedence when policies are deployed at tenant, group, and user level
Managing AI Trust Layer policies
Settings for Studio Web Policies
Operate the AI Trust Layer in production.
Configure the LLM Name for a model outside the predefined list of recommended models
Connecting custom LLMs through AI Trust Layer
Data residency and supported models
Apply third-party model policies and explain why requests may still be served
Managing AI Trust Layer policies
Restricting LLM calls to your own models
Describe behavior when a custom LLM configuration stops working after a provider-side change
Connecting custom LLMs through AI Trust Layer
Configure access to an on-premises model with no public endpoint
Connecting custom LLMs through AI Trust Layer
How-to guide: Connecting open-source models through AI Trust Layer
Apply observability and runtime monitoring.
Interpret Agent Score and its components, and the effect of Recalculate
Managing runtime evaluations (Preview)
Explain score movement after a prompt-only or tools-only revision
Apply Automation Ops policies that enforce a minimum Agent Score across versions
Settings for Studio Web Policies
Managing AI Trust Layer policies
Maintain release records across controlled iterations of prompt, tools, input schema, and evaluation set
Apply reliability and operational resilience practices.
Use Orchestrator job traces to diagnose the behavior of a production agent
Apply change control after correcting an agent that is part of a Studio Web solution
Publishing and deploying solutions
Wrapping Up UiPath Certified Professional Agentic Automation Builder Professional
This guide covered all seven domains of the UiPath-AABPv1 UiPath Certified Professional Agentic Automation Builder Professional exam, from agentic foundations and deterministic automation to Maestro orchestration, coding agents, and AI governance. Work through each linked page, practise in Studio Web, and you will be ready to pass. You can also explore more UiPath certification study guides on the UiPath category to keep building your skills. Have a question or tip? Leave a comment below.
Receive Updates on UiPath Certified Professional Agentic Automation Builder Professional Exam
Want to be notified as soon as I post? Subscribe to the RSS feed / leave your email address in the subscribe section. Share the article to your social networks with the below links so it can benefit others.
