Douyin cracks down on fake "former employees": Why is work experience at top-tier large companies so highly valuable?

On September 11, Douyin's official notice account "Douyin Blackboard" publicly named the workplace blogger "Guangyu Ocean".

According to Douyin's statement, the account operator Chen joined Douyin's local life service business at the end of 2023, and was persuaded to leave less than 5 months later for failing to meet the performance requirements during the probation period. After leaving, he claimed on social platforms that he was "former head of local life service CKA of ByteDance Guangdong", and boasted that he once "led the team to rank first nationwide". Douyin denied all these claims and stated that it is preparing to file a lawsuit against him.

When I saw this official notice, what interested me the most was not how much false information was mixed in his resume. That is of course important, but there is another detail worth pondering. A person who worked at ByteDance for less than 5 months, two years later when he started offering workplace consulting services, the most useful professional label he could use was still "former ByteDance employee".

Moreover, it is not enough to just say "I have worked at a large tech company". On social platforms, people also talk about what happened inside the large tech companies, discuss performance evaluation, management rules, and those hidden norms and absurdities that outsiders do not know. The first type of narrative proves that the speaker is qualified to comment on relevant topics, while the second type of narrative makes more people willing to listen to them.

The prestige of large tech companies does not expire after employees leave. In many cases, the experience of leaving a large tech company itself becomes the starting point of the next phase of content creation.

Similar stories have been circulating for many years. 996 work schedule, PUA, involution, screw, age 35 workplace threshold, quitting job without new offer, new buzzwords keep popping up every once in a while. In June this year, a former DingTalk product manager wrote a 70,000-word long article *Working Inside DingTalk*, which was soon followed by *Working Outside DingTalk*, *Working Inside Meituan*, *Working Inside Xiaomi*. One person's work review gradually became a text that a large number of employees of large tech companies could relate to.

This is exactly the strange point: as the stories about harsh work experiences get more and more bitter, the number of people queuing up to enter large tech companies has not decreased significantly.

From January to April 2026, the number of newly posted jobs in the new economy sector increased by 22.6% year on year, among which AI-related jobs surged 8.7 times, and ByteDance still ranked first in the number of newly released positions. The average monthly salary of AI scientists and team heads has exceeded 130,000 RMB. Large tech companies are definitely not out of date. At least in terms of salary, technical environment, resume value and career opportunities, they are still one of the most competitive high-value "tickets" in China's job market.

Over the years, I have interviewed a number of people who joined large tech companies, and also talked with many who left. Some people switched to the insurance industry after working in the internet sector for several years, some left ByteDance to do content creation, and some started their own one-person company or launched startups. During the interviews, I paid more attention to why each person made that specific choice. When I looked back at these interview materials a few years later, I found that they were all essentially calculating the same account.

Why is the work experience at large tech companies so valuable?

We can rephrase this question: when a person devotes the best years of their time, ability and energy to a company, what is the thing that can truly stay with them in the end?

Growth

In the most prosperous years of large tech companies, few people seriously calculated the "return on suffering" of a job.

Around 2015, when a young person joined an internet company in Beijing, Hangzhou or Shenzhen, what they got was far more than a salary. The mobile internet industry was still expanding, new businesses kept emerging, companies were scaling up, departments were expanding accordingly, and new management positions were also increasing. An ordinary employee, as long as they stayed in the game long enough, could move up the career ladder along with the growth of the organization.

Wu Xiaodong entered the internet industry exactly at that time. In 2015, after graduating with a postgraduate degree from a group of top 985 universities, he joined a news and information platform. Within three years, he was promoted from a frontline employee to the head of a project team managing more than 10 people. In 2018, he joined another leading audio internet company. The office was equipped with a gym, employees could arrange flexible working hours, and overtime taxi fares were reimbursed. The company advocated a young, flat and efficient working culture.

Similar working settings were not uncommon at that time. What really attracted people was not just the benefits, but the signal behind it: a new working model different from the danwei system of the older generation was taking shape, where young people could exchange higher work intensity for faster career advancement.

This confidence was supported by real and substantial growth. By 2020, the business revenue of internet and related service enterprises above designated size across China reached 1.28 trillion RMB, up 12.5% year on year; the revenue of the software and information technology service industry reached 8.16 trillion RMB, up 13.3% year on year, with the total number of employees reaching 7.047 million.

The expansion of leading companies was even more notable. Tencent's revenue grew from more than 100 billion RMB in 2015 to 482.064 billion RMB in 2020. In 2020 alone, the number of its employees increased from 62,900 to 85,900. Alibaba's full-time employees grew from about 50,000 at the end of March 2017 to more than 100,000 at the end of June 2019. ByteDance's revenue reached 236.6 billion RMB in 2020, up 111% year on year, and it had 110,000 formal employees by the end of that year.

For an ordinary employee, these figures meant that new positions were constantly created inside the company. New products needed responsible persons, new businesses needed teams, and new managers were required as teams expanded. While the company expanded outward, it also opened up space for individual career upward mobility. It would be very difficult for Wu Xiaodong to be promoted to manage more than 10 people in three years in an industry where the organizational boundary remains fixed for a long time.

Therefore, the appeal of large tech companies in the early years was never just high salary. They were more like a high-speed ascending elevator. Some people joined as product managers, operation specialists or engineers, and two or three years later they were already leading teams, managing budgets and holding real power. Soon, salaries rose along with job levels, and after the company went public or its valuation increased, stocks and options brought additional new income. Even if people did not achieve financial freedom, the large tech company experience itself would increase the salary offer of their next job.

I interviewed a number of people who left large tech companies, and few of them thought they got nothing from those years.

Li Yirong switched from the online education industry to the internet sector, and her last stop was ByteDance. After leaving to start her content creation business, she still recognized the training of logical thinking ability and working methods provided by large tech companies. When I later studied entrepreneurs with ByteDance work experience, I saw similar traces. Some are developing AI video products, some are making design tools, and others are focusing on AI coding, infrastructure and manufacturing. Their businesses have long been separated from ByteDance, but the awareness of rapid iteration, user feedback and efficiency has flowed into their new companies along with them.

What large tech companies truly provide is a set of compound returns that are hard to price on the day of onboarding. In addition to salary, job level, equity, personal ability and resume value all appreciate as the company grows. The company wants to expand as quickly as possible, and employees want to complete their career accumulation as soon as possible. The two sides shared the same development direction for a long period of time. The faster the company grows, the shorter the waiting time for individuals to get returns.

The unique working language of the internet industry was also formed in this environment. Terms like "wartime state", "co-founding", "horse racing mechanism" sound a bit ironic today, but they had real practical basis in the growth cycle back then. The companies were really scaling up, and some employees did get returns far beyond their fixed salary.

High-intensity work thus formed a self-consistent exchange logic. Employees devote more time, the company pays salaries, and also provides a potentially more valuable future. As long as the growth continues, working for a few more years is not just selling more time, but also accumulating a kind of career asset that keeps appreciating.

This also explains why the pain of working at large tech companies in the early years did not form such a widespread public narrative as today. The pain has always existed, but one promotion can re-justify the overtime work in the past year, one stock return can re-justify the high pressure of several years, and an increasingly impressive resume is enough to make people believe that temporarily sacrificing personal life is still a worthwhile deal.

Companies need employees to believe in growth, and individuals also achieve their own upward mobility by riding on the growth of the company. As long as the two growth curves point to the same direction, tiredness can be called "struggle", and overdraw of personal energy can be understood as "investment".

The hardship did not disappear. It was just that the future was valuable enough at that time to pay for the present hardship.

Misalignment

In 2022, when I interviewed Li Xiaotong, she had already left the internet company and worked as an insurance broker for several months.

Li Xiaotong graduated from Peking University Law School, and worked in the media and film industry for many years. In her 30s, she joined the marketing department of a leading internet company and stayed there for 4 years. During those years, she often got off work late at night, and her child was already asleep when she got home. Her physical condition gradually deteriorated, her health indicators in medical reports got worse and worse, and she eventually got seriously ill. After leaving, she did not look for a new job at another internet company, but switched to the insurance industry. In the past, the company had already prepared the brand, budget and organizational resources, and what she needed to do was to complete the project. After working in the insurance industry, she had to figure out where to find clients, why clients would trust her, and how to close each insurance policy all by herself, building everything from scratch.

Around the same time, I also interviewed Zhou Jie. In 2021, she joined a leading big data company to do marketing work, but encountered an organizational restructuring less than three months later. After her work was suddenly interrupted, she did not immediately return to her hometown in Sichuan, but stayed alone in the rental apartment in Beijing to keep looking for jobs, and later also joined the insurance industry. Wu Xiaodong worked in internet companies for a longer time, rising from a frontline employee to a team leader, with his assessment indicators shifting from traffic volume to revenue. He later told me that he hoped to find a job where "income and experience grow proportionally over time".

When I looked back at these people a few years later, I realized that what they were really worried about was not necessarily just overtime work. Li Xiaotong was calculating how long her body could bear the high-intensity work, Zhou Jie found that organizational changes could quickly disrupt personal career plans, and the question Wu Xiaodong raised was more far-reaching: after a person has invested many years in a certain industry, whether the experience accumulated in the past can continue to help them in the rest of their life.

The labor contract can clearly specify the salary and position, but it can hardly list all the returns that a person truly expects when joining a large tech company. Many young people are willing to endure high-intensity work, with the default expectation of another set of long-term benefits: their experience will increase, their position may rise, and their value in the labor market will also improve accordingly. The company pays current-period salary, but what the employees actually bet on is their entire career.

The problem lies in that the two sides are operating on two different timelines.

Companies can adjust their development directions. When the growth of a product stagnates, they can cut down investment; when new technology opportunities emerge, budgets and personnel can be quickly reallocated. Capital naturally chases higher returns, and companies must constantly adjust their resource allocation.

Individuals do not have the same ability. A person who has worked in a certain business line for five years cannot migrate all the experience of these five years to a new growth direction just because the company changes its strategy the next day. The company can abandon a project, but the person has to move forward with all the experience they have already accumulated. For the company, a strategic adjustment may just be a reallocation of resources, but for the individual, it may mean that the career capital accumulated in the past few years needs to be revalued.

The job market in 2026 has made this difference even more obvious. From January to April this year, the number of newly posted jobs in the new economy sector increased by 22.6% year on year, AI-related jobs surged 8.7 times year on year, and their proportion in all newly posted jobs rose from 2.78% to 22.03%. The average monthly salary of AI scientists and team heads has exceeded 130,000 RMB, and ByteDance still ranks at the top of the list of companies with the most active recruitment. The internet industry has not lost opportunities, but the opportunities are increasingly concentrated in new directions.

At the same time, traditional positions are facing new efficiency tests. A 2026 survey by Maimai shows that 95.11% of practitioners in the new economy sector have used AI tools, 38.51% of programmers said their companies have included AI proficiency into performance appraisal, and 54% of surveyed programmers said their companies had carried out workforce optimization in the past year.

The changes brought by AI are therefore not just about how many positions will be replaced. It is also accelerating the depreciation of professional experience. In the past, an engineer with 10 years of work experience usually meant that they had handled more projects, mastered more systems, and had higher market value. After the new technology cycle arrives, the correlation between working years and professional value gradually loosens. Some experience is still scarce, while some other experience may quickly become outdated knowledge that only supports maintenance of old systems.

An increasingly obvious time misalignment has thus emerged between companies and employees. Companies consider the most efficient resource combination for the next stage, while individuals have to consider their full career life cycle. Companies can shift budgets to the AI track, but employees have to bear the cost of skill migration by themselves. Companies can bet on several directions at the same time, but individuals usually only have a limited number of years to place their career bets.

This is also why high salary can no longer fully explain the appeal of large tech companies. Salary determines the labor price of today, but many people are worried about their personal value of tomorrow. A company can continue to make profits, a business can continue to grow, but a certain position inside it may lose its value.

I call this account the "return on suffering". It is not salary divided by overtime hours, but a calculation of how much of the consumption a person bears for the job can finally precipitate into assets that still belong to the individual after they leave the organization. If high-intensity investment can increase the chips for the next career choice, the hardship has the attribute of investment; if the investment returns to zero along with the end of the project, the hardship is more and more close to pure cost.

Looking back at Li Xiaotong, Zhou Jie and Wu Xiaodong, they are facing different versions of the same problem. Li Xiaotong found that career growth cannot overdraw physical health indefinitely; Zhou Jie found that personal career plans are difficult to resist sudden changes of organizational direction; Wu Xiaodong's phrase "income and experience grow proportionally over time" has actually pointed to the core of the problem.

The most attractive part of large tech companies in the past was that organizational growth could be converted into individual growth. Now, this conversion is becoming more and more unstable. More and more people are learning AI, operating personal social accounts, doing side businesses, or preparing for the next career path in advance. Essentially, they are all doing the same thing: reducing long-term bets on a single organization, and keeping more career capital in their own hands.

A company can abandon yesterday's strategy and look for new growth tomorrow, but a person cannot relive their yesterday all over again.

This time difference eventually becomes the hardest cost to hedge between large tech companies and their employees.

Loss of Control

In June this year, a 75,000-word long article leaked from Alibaba's internal corporate network.

The author Teng Yaxin, with the flower name Yousu, is the core product manager of DingTalk's AI product ONE. After ONE was launched, its daily active users once reached 3 million, before experiencing downsizing and business