Agent

Pronunciation: /ˈeɪdʒənt/

An AI system that can perceive its environment, make decisions, and take actions to achieve goals autonomously.

Plain English Explanation

An AI agent is a system designed to pursue goals independently. Unlike a simple chatbot that only responds to prompts, an agent can plan steps, use tools (search the web, run code, query databases), observe results, and adjust its approach — much like a person working through a task.\n\nAgents combine language models with reasoning loops and tool access to handle complex, multi-step workflows.

Analogy

An AI agent is like a personal assistant who does not just answer questions but actually picks up the phone, makes reservations, and follows up — taking initiative to complete tasks rather than waiting for the next instruction.

How is it used?

Agents are used for automated research, code generation and debugging, customer service workflows, data analysis pipelines, and personal productivity tools.

Real-world Example

An AI agent tasked with planning a trip might search for flights, compare hotel prices, check weather forecasts, and compile a detailed itinerary — calling different tools and APIs along the way without human intervention at each step.

Common Misconceptions

Agents are not fully autonomous or infallible. They can make errors, get stuck in loops, and require human oversight for important decisions.

History

AI agents evolved from early expert systems through reinforcement learning agents (DeepMind's game-playing AI) to today's LLM-powered agents with tool use (2023–present).

Related Terms

LLM MCP Prompt