Prompt Engineering for Automated Evaluation: Making LLMs the Judge in AI Builder Solutions

Bala Madhusoodhanan Posted on May 25 Prompt Engineering for Automated Evaluation: Making LLMs the Judge in AI Builder Solutions # aibuilder # powerplatform # evaluation # powerfuldevs PP-AI Builder series (8 Part Series) 1 Supercharge Custom Data Entity Extraction using Bring your Prompt with AI Builder 2 STRIDE into Security: Automating Threat Analysis with Power Platform ... 4 more parts... 3 Handling Unintended Queries with AI Builder in Copilot Studio 4 From Extraction to Assurance:Extraction Meets Evaluation 5 Scaling Prompt Engineering QA with AI Builder 6 Prompt Optimization for AI Builder: Lessons from TOON vs Text 7 Querying Dataverse Using AI Builder’s Grounded Prompts 8 Prompt Engineering for Automated Evaluation: Making LLMs the Judge in AI Builder Solutions Intro : Automated evaluation is fast becoming a necessity as AI-driven agents proliferate across business processes. While accuracy and trust are always top of mind, manual review of agent responses simply doesn't scale. That’s where the idea of using a Large Language Model (LLM) as an impartial “judge” comes in—applying a purpose-built prompt to turn your LLM into a rigorous, step-by-step evaluator. I've previously experimented with extraction and evaluation frameworks which focused on structured data and document extraction. From Extraction to Assurance:Extraction Meets Evaluation Bala Madhusoodhanan Bala Madhusoodhanan Bala Madhusoodhanan Follow Aug 18 '25 From Extraction to Assurance:Extraction Meets Evaluation # aibuilder # powerautomate # powerplatform # llm 6 reactions Comments 1 comment 3 min read However, this article is centered on a different challenge: evaluating conversational, Retrieval-Augmented Generation (RAG) based agents. Let me share a battle-tested evaluation prompt designed for these agents. Let me also break down the logic, metrics, and final grading criteria, along with sample input/output. This approach fits naturally into Power Platform AI Builder scenarios, enabling scalabl