This learning plan guides you through the complete journey of building, configuring, and evaluating intelligent agents in UiPath Studio Web, with a strong focus on Generative AI (Gen AI) activities and scalable evaluation strategies.
Start by exploring the fundamentals in Build your first agent with Studio Web, where you’ll create your first intelligent agents using both no-code tools and Autopilot. Then deepen your knowledge with Agentic prompt engineering, learning how to design effective prompts that guide AI agents to generate useful, accurate, and structured outputs.
Next, in Configure context and escalations for agents, you’ll take your agents from functional to enterprise-ready—grounding their responses in business context and designing escalation flows for human-in-the-loop scenarios. Finally, with Configure evaluations for agents, you’ll learn how to test and refine your agents using structured evaluation sets and powerful scoring methods like LLM-as-a-Judge, Exact Match, and JSON Similarity.
By the end of this learning plan, you’ll be able to confidently build and deploy Studio Web agents that are reliable, context-aware, and evaluation-driven.
All courses in this learning plan use the Community version of UiPath Studio Web.
Before starting this learning plan, you should:
Be familiar with basic automation concepts (e.g., variables, workflows, control structures)
Have access to UiPath Studio Web through Automation Cloud
Be open to learning through hands-on projects and experimentation
Recommended prep courses:
Introduction to Agentic Automation
Introduction to Automation
This learning plan is designed for:
Automation Developers and Technical Professionals building agents in Studio Web
Business Users and Citizen Developers exploring Gen AI use cases
Anyone looking to implement AI-powered decision-making, prompt engineering, and structured agent evaluation
The plan includes four structured, hands-on courses:
Build your first agent with Studio Web
Configure agents using Autopilot and from scratch
Understand core agent components: tools, prompts, contexts
Build a transcript processing agent
Learn agent scoring and evaluation basics
Agentic prompt engineering
Learn zero-shot, few-shot, and chain-of-thought prompting
Apply system vs. user prompts for autonomous agents
Explore prompt health scoring and optimization
Configure context and escalations for agents
Implement grounding with storage buckets
Build escalation apps using Action Center
Design multi-agent flows combining AI and human decisions
Configure evaluations for agents
Create evaluation sets and reusable evaluators
Use Gen AI scoring with LLM-as-a-Judge
Track agent health and ensure enterprise readiness
By the end of this learning plan, you should be able to:
Build agents using UiPath Studio Web with no-code and Autopilot
Craft effective prompts to guide LLM behavior and agent actions
Design agents that respond using context and escalate to humans when needed
Configure robust evaluation strategies using Gen AI and structured scoring
Optimize agent performance and readiness for production environments