Building and Testing AI-Agent Powered LLM Applications: A Live Demonstration [Spartans Summit 2025]

LambdaTest's Spartan Summit 2025 session explored AI agent-powered Large Language Model (LLM) applications, focusing on Retrieval-Augmented Generation (RAG). RAG enhances LLMs by retrieving relevant documents before generating responses. However, it has limitations, including restricted data access and lack of decision-making capabilities. To overcome these challenges, Sai Krishna introduces AI agents, which add a layer of intelligence over basic retrieval models, enabling dynamic decision-making, external tool integration, and handling complex workflows. The session demonstrated an application that utilizes RAG techniques to fetch relevant information from a PDF document and enhance responses using external sources when needed. The application showcases how AI agents can be used in testing to automate repetitive tasks, integrate with JIRA to generate test cases, and analyze logs and errors from CI/CD pipelines. Sai emphasized the importance of ensuring reliability and accuracy of AI agent responses across different scenarios, designing vector databases, and implementing best practices for testing applications to handle bias and ethical concerns.