What is an AI Agent?

A Simple Analogy

Imagine you need to arrange a business trip:

Regular AI (ChatGPT): You ask it "Help me plan a business trip from Beijing to Shanghai," and it gives you a list of suggestions. But you still have to book the flight, hotel, and email colleagues yourself.

AI Agent: You tell it "Arrange a business trip to Shanghai on March 15th, with a budget under 5000 yuan," and it will automatically check flight prices, compare hotels, send calendar invites, and notify relevant people — no manual steps needed.

💡 In a nutshell: ChatGPT is a consultant, Agent is an employee who gets things done for you.

Three Key Capabilities of an AI Agent

1. Perceive

Agents can receive multiple types of input: text, images, files, web pages, code…

2. Plan

Faced with a complex goal, the Agent automatically breaks it down into multiple steps, deciding what to do first and what to do next.

3. Act

Agents can use tools: search the web, write and run code, control a browser, read and write files, send emails…

Why 2025 is the Year of the Agent?

Three key breakthroughs happened simultaneously:

Model capability leap: Models like Claude 3.5 and GPT-4o have reached a threshold where their reasoning ability can reliably complete complex tasks.

Tool ecosystem matures: The MCP protocol standardizes tool integration, with over 500 MCP Servers now available.

Infrastructure improves: Platforms like Dify and LangChain lower the barrier to developing Agents.

Common Agent Types

TypeRepresentative ProductsKey Capabilities

General AutonomousManus, OpenClawCan complete any open-ended task Software EngineeringDevin, CursorWrite code, fix bugs, deploy Research AssistantDeep Research, PerplexityInformation gathering and analysis reports Workflow Automationn8n, DifyConnect multiple systems for automated workflows