In this session of the Predictable AI Placement series, Jay Stewart, Solution Consultant Fellow at Pega, takes a deep dive into the Assignment Assist Agent—a case‑level conversational agent designed to support subject matter experts during active assignments.

Building on the earlier placement patterns in the series, this session focuses on how an Assignment Assist Agent can be embedded directly into the user experience to enable deeper analysis without disrupting the flow of work. Using a compliance and audit use case, Jay shows how this agent supports analysts after automated analysis has already been performed by document and step agents.

You’ll see how the Assignment Assist Agent:

• Appears contextually during a specific assignment (for example, assessment review)
• Uses knowledge tools backed by data pages to access audit findings and audit rules
• Provides guided, conversational insights into documents and findings
• Helps subject matter experts explore details and validate conclusions before finalizing their work

The session also walks through how to design and configure the agent in Dev Studio, including:

• Agent instructions, guardrails, and tone
• Quick‑select questions for guided exploration
• Knowledge tools and example phrases
• UI placement options (utilities panel, tab, or case‑level agent icon)
• Visibility rules to ensure the agent appears only when it adds value

Importantly, Jay emphasizes best practices for using Assignment Assist Agents responsibly—ensuring they increase efficiency and quality without unintentionally extending cycle time.

This deep dive is part of the broader AI Expert Circle series covering the five AI placement patterns and follows earlier sessions on the Application Agent, Document Agent, and Step Agent, with a final deep dive on GenAI Connect coming next.