Build an agentic RAG assistant with Elasticsearch

Want to see what it really takes to build a smart AI assistant? How about one that can help you make the right fantasy basketball picks? In this live coding session, we’ll build a RAG agent with Elasticsearch, Mastra, and JavaScript — and show how it can power real-world use cases like smarter player picks.

Join JD Armada, developer advocate, for a 20-minute live coding session to learn about: - Defining agent logic, tools, and system prompts with Mastra - Creating a React-based chat interface with markdown-formatted output (e.g., compare LeBron and Curry) - Using tool calls to dynamically compare player stats - Tracking token usage and tool execution for observability and cost control - Deliver dynamic recommendations — like which free agent to pick up for your fantasy team

Key Highlights: - Live demo of an AI assistant that returns real-time, stat-based comparisons - Walkthrough of integrating LLM-powered agents with front and backend components - Monitoring agent behavior with token and tool usage tracking

Resources: - Search Labs Elastic's blog for developers and data scientists: https://www.elastic.co/search-labs/blog/agentic-rag If you’re looking to build smarter AI agents with real-time data, this session is for you. Jump into the chat, follow along, and see what’s possible with Elasticsearch.