ChatGPT Agent Mode Usage Tutorial, 2026 Automated Task Practical Getting Started Guide

One of the hottest topics in the AI ​​circle in 2026 is that ChatGPT is no longer just a conversational robot, but has become a "digital employee" who can check information online, read and write documents, and call third-party services. The Agent Mode (also called automated task mode) launched by OpenAI allows ordinary users to use natural language to send AI to do a series of complex things. The question is, how to enable this mode, what is it suitable for, and what pitfalls should be avoided. This article will start from scratch to help you complete the first Agent task in your own account.

1 What is ChatGPT Agent Mode?

Agent Mode is an execution capability extended by ChatGPT on top of the standard conversation mode. You give it a goal, such as helping me compare the entry prices of three cloud service providers and organize it into a table. It will plan the steps, open the browser, read the web page, organize the results, and finally hand the finished product back to you.

Different from the past interaction where you asked and it answered, Agent Mode introduces multi-step reasoning and tool invocation. In a task, it may have to open multiple web pages, save intermediate results, call calculation or document tools, and then give the final answer. The whole process is basically transparent to the user, you only need to see which step it is executing and the final result.

To simply understand, the normal dialogue mode is question and answer, and the agent mode is delegation. In the former, you control the rhythm, and in the latter, it runs on its own after you hand over the tasks. Each of the two modes has its applicable scenarios. If you understand this difference, you will understand the value of Agent Mode.

2. What is the difference compared with ordinary dialogue mode?

The most intuitive difference is the granularity of tasks. The normal conversation mode is suitable for small tasks such as asking and answering questions, such as changing a paragraph of text, translating a sentence, and explaining a concept. Agent Mode is suitable for processing complex tasks that require multiple steps to complete, such as conducting an industry survey, organizing a comparison table, and drafting a report with data support.

The second difference is the initiative of the AI. In normal conversations, the AI ​​responds passively and won't move unless you ask. In Agent Mode, the AI ​​​​executes actively. After receiving the task, it will dismantle the steps by itself, judge by itself whether to check the information, and decide when to stop. It will tell you the progress during the process, but it will not ask you what to do at every step.

The third difference is tool usage. Agent Mode has built-in browser, document processing, code execution and other tools, which can be called on demand during tasks. Although the normal conversation mode can also call some tools, the frequency of calls and the combination ability are far less than those of the Agent Mode.

The fourth difference is time cost. An Agent task may take several minutes or even longer because it involves multiple network requests and reasoning. Ordinary conversations are basically responded to within seconds. You must be aware of this. Agent Mode is not used to pursue speed, but to pursue the completeness of results.

3 Prerequisites for turning on Agent Mode

Agent Mode is currently open to paying users. For details about which plans are supported and whether there is a limit on the number of tasks, please refer to the official page announcement. As of the writing of this article, the industry generally believes that both individual Plus users and team Team users can see this entrance in the client, but the functional details will change with version updates.

In terms of equipment, it is recommended to give priority to the official client or web version of the desktop version. Although the mobile version can also be used, it is inconvenient to see the progress due to the small screen. The network environment needs to be stable, because the Agent needs to access external web pages multiple times during execution, and network jitters will cause task interruption or timeout.

You should also pay attention to account security. If you plan to let Agent operate a website that requires login to access, be careful when it comes to account authorization. Do not directly hand over highly sensitive accounts (banks, internal corporate systems) to AI for operation. Safety precautions will be discussed separately later.

If you still can’t see the Agent Mode entry in your account, there may be two reasons. One is that your subscription level has not unlocked this ability, and the other is that the function has not been fully released in your area. If you wait patiently for a few weeks, it will usually be opened one after another. There is no need to go out and find third-party activation channels. Most of those channels are scams.

4. Breakdown of the actual steps of the first Agent mission

Let’s walk through the entire process with a specific example. Task setting: Help me find out the prices of entry-level virtual machines for individual developers from three mainstream public cloud service providers, organize them into a comparison table, and point out which one has the highest cost performance.

The first step is to switch to Agent Mode in the ChatGPT client. Generally, there will be a mode switch button or tool menu near the dialog input box. Find the Agent or Tasks related options and click on them. If you are not sure where it is, you can directly ask ChatGPT how to turn on Agent mode, and it will give the specific path to the current version.

The second step is to clearly enter the task description. This step is the most critical. Don't just write "Help me compare cloud service provider prices", but clearly state the scope, goals, and output format. For example: Please check the current monthly prices of Alibaba Cloud, Tencent Cloud, and Huawei Cloud's three entry-level cloud servers (1 core, 2G internal storage space) for individual users, organize them into a table containing four columns: manufacturer, configuration, price, and remarks, and use a paragraph below the table to comment on which one is the most cost-effective.

The third step is to confirm the task and start it. The Agent will display the tasks and rough plans it understands, and you can confirm or fine-tune them. After starting it, let it run by itself. During the process, you will see which pages it opens and what information it extracts.

The fourth step is to review the results. After the task is completed, do not use it directly without looking at it. To check the origin of each number, the agent sometimes gets an outdated snapshot of the page or reads the wrong field. Treat the result as a first draft, check the key data yourself again, and make sure it is correct before using it.

5. Several principles for writing Agent instructions well

The first principle is to state the goal clearly, not the process. Novices can easily get caught up in the details of directing the AI ​​to do each step, which in turn limits the Agent's performance. You only need to tell it what results you want, how to check it specifically, and how to sort it out.

The second principle is to give a clear output format. Whether you want a Markdown table, a plain text list, or an exported file, make it clear in advance. Otherwise, the format selected by the Agent may not be what you want, and you will have to rework it later.

The third principle is to limit the scope. If you only care about a few manufacturers or a certain region, name them in the command, otherwise the Agent may expand to a lot of information you don't need, which is slow and expensive.

The fourth principle is to give verification criteria. For example, all prices must indicate the currency and time, and all references must provide source links. This self-examination requirement can force the Agent to do a more solid job and reduce the probability of compiling data based on impressions.

The fifth principle is to allow it to stop and ask you. You can add a sentence to the task: If you encounter an uncertain key judgment midway, please stop and ask me first. This can prevent the Agent from running too far in the wrong direction and only discovering that it has gone astray when the task is over.

6 Typical Scenarios Suitable for Agent Mode

Multi-source information aggregation is the most typical scenario. For example, collect several recent headline news in a certain industry and organize them into summaries, compare the functional differences of multiple products, and research introductory knowledge in an unfamiliar field. These things originally require you to open a dozen tabs and look at them slowly, but the Agent can finish them in one go.

Documentation is also great. Give the Agent a long document and ask it to summarize the key points, extract key data, rewrite it in another style, and translate it into another language. This kind of task can also be done in normal conversation mode, but the advantage of Agent Mode is that it can handle more materials at one time without you having to switch contexts back and forth.

Competitive product analysis and market research. Let the Agent find several major competitors of a certain product, compare their pricing, functions and user reviews, and organize them into a report. This kind of task used to take a day or two to do manually. The Agent can produce a first draft in a few dozen minutes, and you can just revise it later.

Simple data collection and cleaning. For example, extract specified fields from a set of public web pages and organize them into tables. This type of work often required writing scripts before Agent Mode came out, but now it can be explained in natural language, which lowers the threshold.

Drafting work reports and emails. Provide Agent with what you did this week and let it help you write a weekly report based on the company's business background. Agent Mode is also capable of such creative tasks, and the results are often more consistent than pure conversation mode.

7 Scenarios where Agent Mode is not suitable

It is not suitable for queries with strong real-time nature. Agent runs for a few minutes at a time. If you just want to check the exchange rate, check the weather, or find out how to say a certain English word, it is faster to directly have a normal conversation or even direct a search engine.

Matters involving highly sensitive data and decisions are not suitable for Agent to run automatically. For example, we can place large orders on your behalf, automatically transfer funds, automatically sign contracts, and automatically send emails to customers. This kind of thing must be confirmed manually, and the decision-making power cannot be completely handed over to AI. Agent can help you draft it, but you have to do the final sending and confirmation yourself.

Tasks that require long-term memory and stable execution are not suitable. Agent Mode After a single task ends, the status will not be retained by default. If you need a long-term running robot (such as monitoring a website every day and generating a report every week), you should use a real automation platform or API instead of manually opening the Agent once a day.

Websites involving login status and verification codes may not be able to run smoothly. The Agent's built-in browser is sometimes recognized as an irregular access by the website, triggering a verification code or anti-crawling mechanism. If your target website is strictly protected, the Agent may get stuck halfway through.

Use caution in areas that require professional judgment. For example, in medical diagnosis, legal opinions, and investment decisions, agents can find information but cannot replace real professionals. It's okay to treat it as a documentarian, but it's dangerous to treat it as an expert.

8 Safety and Cost Considerations

The most important thing about security: don’t let Agents access sensitive accounts without your complete monitoring. If a task requires logging into a certain platform, first use a sub-account or test account with minimal permissions instead of using your main account to hand it over directly to the Agent. The scope of authorization can be as narrow as possible.

Be mindful of data privacy. Agent may transmit your input and intermediate results to the server during the task. The specific information that will be recorded and used for training shall be subject to the official policy. Content involving business secrets, customer data, and personally identifiable information should be carefully included in Agent tasks.

In terms of cost, Agent Mode tasks are generally billed based on duration or number of calls. Please see the official page for specific rules. Subscriptions at different levels will have different quota limits, and running too much may trigger current limits or additional charges. It is recommended to practice with small tasks before getting familiar with them, and then deliver important tasks after they run smoothly.

Mission failure is also common. Network problems, website changes, and limitations of the model itself may cause Agent to make mistakes midway. Develop the habit of keeping intermediate logs. When something goes wrong, you will know at which step the crash occurred and how to change the instructions next time to avoid it.

The final hidden cost is the cost of review. The results generated by the Agent cannot be used directly. It takes time to check. If it takes longer to check a task than it takes to do it yourself, then the task is not suitable to be handed over to the Agent at all. Use the right tool for the right task.

9 Advanced Gameplay Workflow Series

After you are familiar with the basic usage, you can try to use Agent in conjunction with other tools.

The first type of series connection is Agent plus automation platform. Connect the trigger conditions and result output of the Agent task to tools such as Zapier Make n8n to achieve true automation. For example, Agent is automatically asked to research industry trends every Monday morning, and the results are sent to the team group. This requires a little configuration effort, but once it's run through, it's completely unattended.

The second type of concatenation is Agent plus custom GPT or custom Skills. Make commonly used task templates into a fixed GPT entry. In the future, you only need to click in and fill in a few parameters to run. Suitable for those fixed processes that need to be run every week.

The third type of series connection is Agent plus local tools. Through the plug-in API or the small tool written by yourself, the Agent calls the local database file system computing service in the task. This step has a high technical threshold, but it can expand the boundaries of the Agent's capabilities.

The fourth type of series connection is the collaboration of multiple Agents. One Agent is responsible for collecting information, another Agent is responsible for organizing it, and another Agent is responsible for reviewing it. Although it increases the complexity, it is more effective on some large tasks than a single Agent running the entire process. This type of gameplay is still evolving rapidly, so you can continue to pay attention to the latest cases from the official and community.

The core idea of ​​the advanced gameplay is to treat the Agent as a link in the workflow, rather than a universal terminal tool. It's good at taking on some steps, but not good at taking on all the steps. Once you understand this, the value of Agent Mode can be fully unleashed.

FAQ

Does Agent Mode need to be paid separately?

Agent Mode is usually included in the paid subscription of ChatGPT. The specific levels supported and whether there are additional times or duration limits are subject to the official account page. Generally speaking, both individual Plus and team Team plans can be used, but the task quota may be different. Free users currently cannot see this entrance and need to upgrade to the paid level first. If you cannot see the Agent entrance in your account, you can go to the subscription management to confirm the current level, or wait for the function to be gradually released in your area.

Can I close the browser while Agent is running a task?

Yes, but the specific behavior depends on the task type. Generally speaking, the Agent task continues to run in the background, and after running, you will see the results the next time you open ChatGPT. However, some tasks that require interactive confirmation may be paused waiting for your return. It is recommended to keep the window open when running for the first time to observe the entire process, and then try to close the background running after becoming familiar with it. If the task takes longer than expected and has not ended, log back in to see if it is stuck at a certain step waiting for your confirmation.

How reliable are the results given by the Agent?

Agent can complete more steps than a normal conversation, but that doesn't mean the result is necessarily correct. It can still hallucinate (make up facts that don't exist), get outdated information, and read the wrong fields. Treat the Agent's output as a first draft, and check all key data and judgments yourself. You must be more cautious when it comes to decision-making. Agents can provide materials and preliminary analysis, but the final judgment must be made by humans. Develop the habit of checking, and the Agent will really help you improve efficiency instead of digging holes for you.

Are Agent Mode and Custom GPT the same thing?

Not exactly. Custom GPT is a set of instructions and knowledge base packaged into a fixed dialogue entry, suitable for handling the same type of recurring problems. Agent Mode emphasizes the multi-step execution capability of a single task and can complete multiple steps in one conversation. The two can be used in combination. For example, common Agent tasks can be made into custom GPTs. Each time this GPT is started in the future, it will automatically enter the corresponding execution process. Only by understanding their positioning differences can you choose the right tool in the appropriate scenario.

How does Agent Mode perform in Chinese scenarios?

Overall it's usable, but there are a few details to pay attention to. First, the parsing of Chinese web pages is sometimes not as accurate as that of English web pages, and the Agent occasionally misidentifies the page structure. Second, some domestic websites have strong anti-crawling mechanisms, and Agents may have limited access. Third, Chinese task descriptions need to be written more clearly, because the model's dismantling accuracy of Chinese long instructions is slightly lower than that of English. It is recommended that in Chinese tasks, use more column points and more parentheses to explain and provide more output format examples, so that the probability of Agent errors will be significantly reduced. The Chinese support for ordinary daily tasks is enough.