Lately, the term "AI agent" keeps popping up everywhere. Whether I'm reading the news or watching videos, everyone's talking about AI agents and the AI agent market, like it's the latest trend.

Everyone's familiar with ChatGPT, Gemini, and the like. But what exactly is an AI agent? Can't we just use ChatGPT? Why create an AI agent in the first place?

Let's start with what an AI agent is. Simply put, it's like an "all-around assistant."

You can chat with ChatGPT, and it can write articles and answer questions. But if you ask it to book a flight or track a package, it'll just shrug its shoulders and say, "I can't do that!"

But an AI agent is different. It can not only chat, but also "get things done." It's as if ChatGPT is a smart brain, but without hands and feet. An AI agent, on the other hand, equips that brain with memory and a body, allowing it to perceive the outside world, remember what it's done, and run off to complete tasks.

Take Manus AI, which has been quite popular recently. If you ask it to write a report, it can plan the steps on its own, search for information online, remember what it's seen, and finally deliver the report to you. With ChatGPT, you'd have to find the information yourself and feed it to ChatGPT before it could even start working.

So, why do we need AI agents? Aren't large language models (LLMs) enough? Actually, LLMs are like "armchair quarterbacks" – they're great at talking, but not so great at taking action. AI agents, on the other hand, are more like "doers" – they can interact with the real world.

For example, if you say, "Help me find a cheap flight to Shanghai for next week," the AI agent will go and search and compare prices on its own, giving you a reliable recommendation. ChatGPT would at most chat with you about the scenery in Shanghai, with hardly any useful information.

So, AI agents add "hands-on skills" to AI, transforming it from someone who just talks the talk to someone who can actually get things done.