What is AI Agent?
An AI system that perceives its environment, makes decisions, and takes actions autonomously to achieve a goal.
Definition
An AI agent is a system that uses a large language model as its reasoning engine to perceive inputs, plan a sequence of actions, use tools (web search, code execution, database queries, APIs), and iteratively work toward a goal without requiring a human to approve each step. Unlike a simple chatbot that only responds to prompts, an agent loops: it acts, observes the result, and decides what to do next.
Why it matters
AI agents are the shift from AI that answers questions to AI that gets things done. In 2025–2026, nearly every enterprise AI initiative is built around agents: systems that can autonomously handle workflows, manage data pipelines, respond to customer inquiries, and complete multi-step engineering tasks. Understanding agents is now a core competency for PMs, engineers, and operators alike.
How it works
A typical agent loop: (1) receive a goal, (2) the LLM reasons about what action to take next, (3) the agent calls a tool (e.g., search the web, run code, query a database), (4) the result is fed back to the LLM, (5) the LLM decides whether the goal is met or another action is needed, and loops. The agent maintains memory of previous steps in its context window.
Examples in practice
Customer support agent
An AI agent receives a support ticket, retrieves the customer's history from a CRM, looks up the relevant product docs, drafts a personalized reply, and if the issue is unresolved, creates a follow-up task — all without human intervention.
Claude Code
Claude Code is an agentic coding tool: given a task like "add user authentication," it reads your codebase, writes files, runs tests, reads the output, fixes failures, and loops until the task is done.
n8n AI agent workflow
An n8n workflow with an AI Agent node can receive an email, classify the intent, route it to the right team, draft a response, and send it — operating as a fully autonomous business process.