Doubao Work launches a 30-day check-in campaign for 8,800 credits — why is it offering free use to netizens nationwide?

Get 8,800 credits: why is Doubao Work inviting netizens nationwide to use it for free? Rryyo, 1 hour ago. Everyone can develop their own Doubao Work method.

Since Doubao Work was launched at the end of August, Doubao has been giving users free benefits almost every month. Recently, Doubao launched another round of benefits: all users who check in for a cumulative 30 days can get 8,800 credits, more than the 8,400 credits provided by the standard plan over four weeks—a generous amount that really fills you up. This activity can be used on both the Doubao desktop app and the Doubao Work desktop app, and paying users will not feel "stabbed in the back," because their credits have also increased substantially.

You should know that, compared with everyday functions such as chat, Q&A, and translation, the tasks carried by office AI are often more complex and consume more tokens. After entering the Agent era, AI can directly operate browsers, process local files, stay on duty in the background for long periods, and even autonomously complete entire workflows, so token consumption is increasing day by day.

Credits, credits, and more credits have become a common demand among users—whether paid or free.

So what exactly can the 8,800 credits Doubao is giving away this time be used for? After the intensive updates over the past two months, to what extent can Doubao Work help us complete our daily work? As a heavy user of both Doubao and Doubao Work, I will try to answer these questions. Another month of benefits: Doubao is becoming more and more generous.

First, let's look at the scale of this benefit.

According to the activity rules announced by Doubao, all new and existing users can receive 200 credits by checking in every day, with credits doubled on Mondays. When cumulative credits reach 500, 2,000, and 5,000, users can also receive additional rewards of 200, 500, and 1,300 credits respectively:

A cumulative 30-day check-in earns 8,800 credits.

For comparison, the Doubao Work standard plan, currently priced at 80 yuan/month (68 yuan/month with continuous monthly billing), provides 2,100 credits every 7 days, totaling 8,400 credits over four weeks; the enhanced plan (240 yuan/month, 200 yuan/month with continuous monthly billing) and the advanced plan (599 yuan/month, 500 yuan/month with continuous monthly billing) provide 5,600 and 14,000 credits every 7 days, respectively. In other words, the cumulative credits given away over 30 days in this activity even exceed the total credits of the standard plan over four weeks.

(Image source: Doubao Work)

Of course, users who have already paid for a Doubao Work subscription do not need to worry: they can participate in the check-in activity, and the free credits obtained can be added to their existing credits and will be consumed first. In fact, these activity credits can even be used for video generation and Pro models.

This round of activity is especially friendly to new users: new users logging in to the Doubao desktop app or Doubao Work desktop app for the first time can directly receive a 30-day free trial plan and can continue to participate in this benefit activity. The specific way to participate is also simple: through the check-in pop-up in the lower-left corner of the Doubao desktop app or Doubao Work desktop app, or by clicking the avatar and selecting "Use Doubao for free" in the sidebar.

It is worth mentioning that, in addition to daily check-ins, Doubao has also set up a series of experience tasks this time. Users who use Doubao Work to organize documents, operate browsers, create tables, invoke skills, and so on all have opportunities to receive more free credits.

From the design of the activity, Doubao does not just want users to open the software once a day to claim a benefit; it hopes even more that everyone will actually put these credits to use, become Doubao Work users, and achieve an upgrade "from beginner to advanced" in professional features. After all, today's AI no longer lacks the ability to answer questions, and using the Doubao App as a daily search tool has become a common choice for hundreds of millions of users. But for most people, using AI, especially Agents, in real work scenarios is still something they have not yet tried. Giving away free credits, bringing AI into workflows, and landing Agents in enterprises are the deeper goals of this round of Doubao activities. From planning topics to analyzing accounts, I have developed my own Doubao Work method.

Doubao Work is indeed worth trying for everyone. If you have not used it yet, you may think I am exaggerating by saying this, but if you have used Doubao Work, you will find that the real charm of AI lies in this: the longer you use it, the greater its potential; the more you use it, the less you can do without it.

As the editor-in-chief of Leikeji, the work I handle every day is very miscellaneous: daily topic planning, manuscript review, content scheduling, project coordination, major reporting projects at specific times such as CES, IFA, and Double 11, and over the long term, attention to the editorial team's content quality, work efficiency, collaboration processes, and member capability improvement. Some of this work requires experience and judgment accumulated over the long term, but many steps are actually very tedious and can even be called mechanical labor.

For example, every morning, an important task for the editorial team is to screen the hot AI hard-tech news worth reporting that day. From AI, Agents, phones, and computers to smart cars, home appliances, and robots, there are large numbers of new product launches, technological advances, and industry developments every day. Sometimes, by the time we finish browsing and screening, it is already past ten in the morning, and determining the day's topics is often too late.

So I started trying very early to have AI Agents take on part of this work, for example, having Doubao Work search every day for hot news in fields such as AI, consumer electronics, phones, home appliances, and robots from the past 24 hours, verify the original sources, then screen out topics worth reporting from the perspectives of timeliness, consumer value, and discussion heat, and provide news facts, reporting angles, and reference materials.

Such tasks generally take only a few minutes and can be completed quite well with a few dozen credits.

After supporting multiple Agents working in parallel, Doubao Work can now simultaneously search for news in multiple fields, cross-check information from different sources, and put together a reference list of the day's topics in less time. For example, when doing a market analysis, Doubao Work can have different Agents separately collect product information, organize industry data, and analyze changes among competitors, rather than working "serially" like a single Agent that finishes one task before starting the next.

Of course, the topics selected by AI cannot be directly equated with the editorial department's final decision. Whether the news is an AI hallucination, which news is worth reporting, from what angle to approach it, and what differentiated angles and incremental information to provide that peer media have not yet offered—all of this ultimately depends on the editor's judgment. But if AI can help me and my editors complete information gathering and initial screening in advance, we can leave more time for truly valuable topic planning and reporting.

For media, the professionalism and accuracy of content are very important. Especially when it comes to products and technologies such as phones, chips, and AI models, release dates, product specifications, prices, technical details, and even data sources can all affect the credibility of an entire article. But manual review is also quite an energy-intensive task: each article involves dozens or even hundreds of information verification points, and even experienced chief editors find it hard to guarantee they can spot every problem every time.

My practice is to have Doubao Work assist in reviewing articles completed by editors, requiring it to verify factual information such as product specifications, release dates, and prices, giving priority to authoritative materials published on manufacturers' official websites and by authoritative media, and finally outputting a list of issues, marked with the location in the original text, the reason for the issue, the severity level, and a verification link.

Generally, Doubao Work only needs to consume a few dozen credits to find some issues that I myself easily overlook, and under explicit requirements, it also follows instructions and does not rewrite the article without authorization.

In fact, it is not just reviewing articles—when I need to review video scripts, weekly work reports, financial data, and other materials submitted by team members, I always try to have Doubao Work "go through them" first.

Moreover, Doubao Work also supports editing local Excel, PPT, and Word files. It can not only read and process local Office files, but my editors and I can also make manual modifications directly in the Doubao Work interface, achieving true human-machine collaboration and team co-creation.

This point is actually very important.

On the one hand, I do not want AI to replace editors in producing the final content, and even less do I want it, in the so-called "optimization" process, to smooth out articles that originally had viewpoints and personality until they are bland and safe. I believe what AI is best suited to handle is fact-checking, typo checking, data comparison, and similar work. As for an article's logic, expression, and judgment—especially values—these still need to be the responsibility of humans. AI will take on more and more work, but humans are always the first responsible party for the work.

On the other hand, how many pages of PPT AI can generate is not important; the ability to support continuous modification around existing files is actually more prominent in practical value. Because for most workplace users, much work often does not start from generating a file from scratch, but rather requires continuous modification, supplementation, and refinement on the basis of existing content.

Beyond content management, another important part of my work is diagnosing and planning the overall direction of the account to ensure the IP's influence continues to grow. Therefore, I need to regularly analyze the account, including communication data (dozens of metrics such as reads, interaction rate, completion rate, and open rate), content data (the number of pieces in different fields, types, and directions), and editorial work quality. I generally do this once a month, organizing, categorizing, and analyzing the hundreds of articles and over a hundred videos published in the past month. Screening and organizing them one by one, then conducting quality ratings—the whole process takes two or three days each time.

Now I am trying to have Doubao Work first conduct preliminary screening based on article type, excluding general news and similar content, then organize and categorize in-depth articles that meet the requirements, and generate reference materials needed for subsequent excellence evaluations. As an auxiliary tool, it can indeed reduce a large amount of repetitive organizing work for me.

When conducting deep analysis that penetrates table content, Doubao Work's multi-Agent parallelism, browser operation, and local Office editing capabilities together demonstrate strong ability: different Agents separately open links to read content, organize data, and analyze content distribution, generating a review report convenient for editorial department discussion with higher efficiency, consuming just over 100 credits throughout the process.

In addition, Doubao Work recently also launched a computer operation recording capability—simply put, an "Agent hand-holding" mode: the user demonstrates a specific operation once, explaining while operating, and lets the AI organize the entire process into a reusable personal skill. For work such as topic collection, data organization, and content management that has relatively clear rules and needs to be executed repeatedly, this is very valuable.

Of course, my exploration of Doubao Work's capabilities may still be just "the tip of the iceberg." Everyone's workflow, work scenarios, and work habits are different. In theory, everyone can explore their own Doubao Work method and train their own version of Doubao Work. After getting everyone to use Doubao Search, we also want everyone to use Doubao Work.

I remember that when Doubao Work was officially released at the end of August, it launched a campaign offering 30 days of subscription benefits for free. In September, it once again gave all users a 30-day subscription, and this time it has rolled out another welfare campaign giving out credits. If we also count the 3-month free subscription offered to university students during the back-to-school season, along with the accompanying learning skills section, Doubao Work has consistently been very aggressive in "inviting everyone to use it for free." Among the many AI products in China, Doubao is relatively the one least short of users. So why does Doubao Work frequently "treat everyone"?

QuestMobile's "2026 Q3 AI Application Market Development Report" shows that in September 2026, the monthly active user scales of Doubao, Qianwen, and DeepSeek were 419 million, 158 million, and 123 million, respectively. Judging from this set of data, AI has in fact become a national-level phenomenon. However, over the past two years, more and more people have become accustomed to asking AI questions, having AI help explain an image, write a piece of copy, or give some life advice... But when it comes to letting AI autonomously operate a computer, process local files, and complete work tasks, many people may still not be very proficient.

The reasons are manifold: some users are not clear about exactly what work AI can accomplish and are relatively unfamiliar with Agent capabilities—"I haven't used it, so I don't know how to use it"; some users are unwilling to explore new tools in work scenarios and simply use whatever tools the company provides; some users are unwilling to "bring their own supplies" to work, and for paid AI, it is hard to directly pay for a subscription without any actual experience.

Therefore, Doubao Work has been trying to provide free credits to solve the difficulty of getting Agents implemented in work scenarios: no matter who ultimately pays, let users start using Agents first and adapt to AI work first. In this campaign, Doubao also combines additional rewards with specific tasks such as document organization, browser operations, spreadsheet creation, and skill invocation, precisely so that while users claim the benefits, they gradually learn about the product's different capabilities. Doubao is not just inviting people across the country to use AI for work for free; it is also teaching people across the country to get used to using AI to get work done.

This reminds me of the recently bustling Double 11. Some people say that Double 11's popularity has declined and user attention is far less than before. To some extent this is true, but it precisely illustrates another point: e-commerce has become a way of life for everyone. Double 11 was born in 2009, when only a very small number of users shopped online. Later, platforms such as Tmall and JD.com used Double 11's "50% off" approach to attract everyone to experience online shopping, while also promoting the improvement of e-commerce infrastructure such as logistics, payments, and cloud computing. It is precisely through such methods that users across the country gradually became accustomed to online shopping. To some extent, Doubao Work giving away free credits is no different from Double 11; the latter promoted the popularization of e-commerce, while the former is intended to integrate AI into everyone's daily work.

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