Lately, the term "AI agent" keeps popping up everywhere. Whether it's news or videos, everyone's talking about AI agents and the AI agent market, like it's the next big thing.

We're all familiar with ChatGPT, Gemini, and the like, but what exactly is an AI agent? Can't we just use ChatGPT directly? Why create an AI agent in the first place?

Let's start with what AI agents are. Simply put, they're like "all-in-one assistants."

When you chat with ChatGPT, it can write articles and answer questions, but if you ask it to book a flight or track a package, it'll shrug and say, "That's beyond my capabilities!"

But AI agents are different. They don't just chat; they can also "do things." It's like ChatGPT is a smart brain without hands or feet, while AI agents equip that brain with memory and a body, allowing it to perceive the outside world, remember what it's done, and go off to complete tasks.

For example, take the recently popular Manus AI. If you ask it to write a report, it can plan the steps itself, search for information online, record what it's seen, and finally deliver the finished product. With ChatGPT, you'd have to find the information and feed it to it before it can even start working.

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

For instance, if you say, "Help me find a cheap flight to Shanghai next week," an AI agent will go and search, compare prices, and give you a reliable recommendation. ChatGPT would, at best, chat with you about the scenery in Shanghai, with little practical information.

Therefore, AI agents add "hands-on skills" to AI, turning it from just talk into something that can actually get things done.