---
title: Agent
description: Page on Vedang Vatsa's site: https://veda.ng/glossary/agent
canonical: https://veda.ng/glossary/agent
last_updated: 2026-09-22
type: text/markdown
---
# Agent

Source: https://veda.ng/glossary/agent
Author: Vedang Vatsa (https://veda.ng/about)

An Agent is an AI system that perceives its environment, makes decisions, and takes actions to achieve goals. It's autonomous. It operates without constant human direction. A basic agent has this loop: observe the environment, decide what action to take, execute the action, observe the results, repeat.

A chatbot answers questions you ask. An agent sets its own goals and pursues them. Modern AI agents are LLM-based. They use language models for reasoning and decision-making. An agent can access tools, APIs, code execution, database queries. It decides which tool to use. It executes the tool. It observes the results. It plans next steps.

For example, an agent might be tasked with "analyze this dataset and find insights." It would plan: download the data, inspect its structure, run statistical analysis, visualize results, summarize findings. It breaks down the high-level goal into tool calls. Each tool call returns information that informs the next decision. Agents accomplish multi-step tasks autonomously. They recover from mistakes. They adapt to unexpected situations. A limitation is agents are expensive. They make multiple tool calls and LLM inference, and can fail catastrophically if they misunderstand their goal or if their tools have side effects. Russell and Norvig define an agent as anything that perceives an environment and acts. That textbook definition is what people now apply to LLM tool-users.

Glossary index: https://veda.ng/glossary