Prompt Engineering for Automated Evaluation: Making LLMs the Judge in AI Builder Solutions
The article discusses the use of Large Language Models (LLMs) for automated evaluation of AI-generated responses. It highlights the importance of scalability and objectivity in evaluating conversational agents. A structured prompt is presented to guide the evaluation process based on specific metrics.
- ▪Automated evaluation is becoming essential as AI agents are increasingly used in business processes.
- ▪The article introduces a prompt designed for evaluating Retrieval-Augmented Generation (RAG) based agents.
- ▪The evaluation rubric includes metrics such as Task Fulfillment, Conciseness, Professional Tone, and Formatting Compliance.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 941014) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } 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...
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