What is an AI Agent? Understanding the AI that Acts on Your Behalf

At 3 pm, a marketing specialist in Taipei stared at her screen. Her boss had asked her to summarize the key points of five competitor websites' redesigns and create a one-page report, just 10 minutes ago. Six months ago, she would have had to open five separate pages, copy and paste, and manually format the text, which would have taken up her entire afternoon. This time, she simply typed out the task to an AI and went to grab a cup of coffee. When she returned to her seat, the browser had automatically opened the five websites, taken screenshots, and written a summary, with a draft waiting for her to review.

This is the fundamental difference between an AI Agent and the chatbots you're familiar with.

Agent and Chatbot: What's the Difference

I'll use an analogy: a chatbot is like a knowledgeable consultant who answers your questions but won't take action on your behalf. An AI Agent, on the other hand, is like an intern who can break down tasks, execute them, and even find alternative solutions when encountering obstacles.

To be more specific, three key capabilities distinguish agents from regular chatbots:

1. Planning: When you ask an agent to "book a high-speed rail ticket to Kaohsiung for next Wednesday," it knows to first check the schedule, compare prices, and then fill out the necessary information, rather than just providing a text-based tutorial.
2. Tool use: An agent can invoke a browser, search, send emails, operate spreadsheets, and even control your computer screen, rather than just generating text.
3. Memory and correction: If an agent encounters an issue, such as a website redesign, it can re-evaluate and adjust its approach, rather than getting stuck.

The chatbots you're currently using, such as ChatGPT, Claude, and Gemini, have already developed agent-like capabilities – they can search the internet, execute programs, and integrate external services. The difference lies in whether you're using them to complete tasks from start to finish or just providing instructions one step at a time.

What Agents Can Actually Do for You

Let's move beyond concepts. I've listed several scenarios that are currently feasible in 2026, and my colleagues and I are actually using them:

• Cross-website data collection and organization: Like the marketing specialist in the introduction, an agent can browse multiple websites, summarize the information, and produce a draft. Research-oriented tools like Perplexity excel in this area.
• Computer operation: A class of "computer operation" agents can directly control your screen, move the mouse, and click buttons to handle tasks that require manual intervention, such as older systems without APIs. CUA and Bytebot are examples of this type of agent.
• In-house assistant for enterprises: By feeding an agent your company's documents and customer service records, it can answer colleagues' questions, fill out forms, and more. Dust is a platform that focuses on this aspect.
• General-purpose agents for complete tasks: You can ask an agent to "plan a three-day, two-night trip to Tokyo, including budgeting," and it will take care of everything from searching for flights and hotels to creating an itinerary. Manus is a representative of this type of general-purpose agent.

If you want to explore more ideas on "what tasks to outsource to AI," we've compiled a list of AI tasks that you can refer to.

How Agents Work (No Programming Knowledge Required)

You don't need to be a programmer to understand the general process, but grasping the basics will help you "command" agents more effectively.

When an agent receives a task, it typically follows this loop:

1. Understand the goal – Translate your spoken language into a to-do list that the agent can understand.
2. Plan the steps – Break down the task into smaller segments, such as "searching, organizing, and producing."
3. Choose the right tools – Decide whether to use a browser, search, send emails, or operate spreadsheets.
4. Evaluate the results and adjust – If successful, proceed to the next step; if not, try alternative methods.
5. Deliver the outcome – Provide the finished product to you.

This "think-do-evaluate-rethink" cycle is what distinguishes agents from one-time responders. Because agents can retry, it's more effective to clearly communicate your goals and acceptance criteria when giving instructions. To practice how to provide clear instructions, you can refer to our prompt template library.

Current Status and Limitations: Don't Treat Agents as Omnipotent

I must admit that, as of 2026, agents are not all-powerful. They excel at executing processes, but there are a few areas where you need to be cautious:

• May confidently provide incorrect information: An agent might misremember numbers or misjudge the location of a button. For tasks involving money, contracts, or external releases, always double-check manually.
• May go off track for complex tasks: The more steps involved, the more likely an agent is to deviate from your original intention. Break down large tasks into smaller segments and verify each part.
• Be mindful of privacy and permissions: Before allowing an agent to access your email or accounts, consider the level of permission you're granting.
• May not always be fast: Some tasks may require an agent to proceed step by step, which can be slower than manual execution. The value of agents lies in "not requiring your presence," not in "speed."

TheAI Academy's Suggestions

My view is that agents won't replace your job in 2026, but they will significantly amplify the difference between those who know how to use them and those who don't. Instead of chasing every new term, pick a repetitive, boring task you do every week – such as compiling weekly reports, summarizing quotes, or tracking competitors – and try to let an agent do it once.

For Taiwanese readers, a practical starting point is to begin with the tools you're already paying for, without feeling the need to install a plethora of new ones. The agent functions of ChatGPT or Claude, combined with a research tool you trust, can cover about 80% of your daily needs. Make "assigning tasks to agents and verifying the results" a habit, which is more important than researching which agent is the strongest.

If you're already familiar with the concepts, the next step is to read our two practical articles: to automate repetitive tasks using AI agents, read Using AI to Automate Your Repetitive Work; to use AI to write code and create small tools, read Coding Agent and Vibe Coding Introduction.

Let's return to the marketing specialist from the introduction. She didn't become an engineer, and she didn't learn any new skills; she simply changed the way she "delegated" tasks – by clearly stating her goals and letting AI take care of the rest. The time it took her to grab a cup of coffee, which used to be the precursor to overtime, is now the time she uses to review the results. AI that can take care of tasks on its own changes not the AI itself, but how you allocate your time.