AI Agent

AI Agent is an autonomous software component that leverages large language models (LLMs) to make decisions, execute workflows, and interact with external systems. It uses reasoning loops to plan and achieve goals without step-by-step human programming.

How it Works

AI agents combine core LLM capabilities with tools, memory, and planning frameworks.

• Reasoning Loop: Uses prompt techniques (such as ReAct) to process inputs, form a plan of action, evaluate intermediate outcomes, and refine steps.
• Tool Integration: Calls external APIs, databases, or calculators to fetch factual information or perform actions, bypassing model training limits.
• Memory Systems: Uses short-term conversation memory and long-term vector memory to maintain context and adapt behavior over time.

Lakehouse & Agentic Relevance

In a data lakehouse, AI agents serve as autonomous analytical assistants. Instead of requiring human engineers to construct complex queries, the agent queries the data catalog, reads metadata, and executes SQL commands directly. Dremio serves as the execution layer for these agents, exposing unified virtual datasets and business-friendly semantic definitions. This integration allows agents to retrieve data securely, execute fast queries, and return answers to user requests in real time.