About the UiPath Agent Builder Technical Updates December 2025 (L200) training

Designed for technical professionals, this advanced module builds on the capabilities introduced in the October 2025 release and focuses on extending how agents ground context, process documents, interact with users, and learn from experience.

You’ll explore just-in-time (ephemeral) context grounding indexes that enable high-throughput document analysis without the overhead of persistent indexes. The course also demonstrates how coded agents can directly access Document Understanding capabilities to perform classification, extraction, validation, and orchestration programmatically within Agent Builder.

In addition, you’ll learn how to configure voice-enabled conversational agents, allowing hands-free, real-time interactions powered by speech-to-text and text-to-speech. The module concludes with deep coverage of agent memory enhancements, including feedback ingestion, escalation-driven memory, runtime memory usage, and memory management; enabling agents to improve accuracy, reliability, and consistency over time.

By the end of this course, you’ll be equipped to build production-ready, intelligent agents that leverage external context, adapt based on past interactions, and deliver more reliable automation across complex enterprise scenarios.

Learning prerequisites

To get the most out of this course, you should have:

• Prior experience with UiPath Studio Web and Automation Cloud.

• Familiarity with agents, context grounding, and Orchestrator concepts.

• A technical background in automation development or solution design.

If you’re new to UiPath Agents, we recommend completing “Build Your First Agent with Studio Web” before taking this course.

Audience

The UiPath Agent Builder Technical Updates December 2025 (L200) course targets Sales Engineers, Automation Developers, Solution Architects, and Technical Consultants enabling them to demonstrate UiPath Agent Builder to customers.

Agenda

The full agenda covers:

• Configuring ephemeral (just-in-time) indexes for context grounding.

• Document processing with coded agents using Document Understanding.

• Designing voice-enabled conversational agents.

• Extending agent context with external vector databases (BYOVD).

• Agent memory enhancements, including feedback, escalation-based memory, and runtime utilization.

Learning objectives

By the end of this course, you should be able to:

• Implement ephemeral indexes for scalable, on-demand context grounding.

• Use coded agents to execute end-to-end document processing workflows.

• Configure and test voice interaction in conversational agents.

• Extend agent grounding using external vector databases.

• Manage and leverage agent memory to improve learning, reliability, and decision-making.