Author: LatePost by WanDian

17-year-old AI intern earns 5,500 yuan daily; those born in 1998 are considered "mid-level veterans"

A well-known venture capital firm established over 15 years ago specially hosted a dinner. The invited guests, targeted by invitation only, did not wear suits and ties; most wore black, white, or gray T-shirts or hoodies with cartoon prints on the chest, their hair casually styled. Many carried backpacks, as if attending a class reunion.

They are post-2000s AI practitioners, most of whom like to use anime or cartoon characters as avatars, are accustomed to using emojis and exclamation marks, and during work breaks, amid a flurry of iced Americano orders, they might order a cup of marshmallow hot cocoa. Before meeting a post-2000s AI entrepreneur, an investor reminded us that to quickly close the distance, it’s best to bring him two cups of milk tea.

Just after completing their undergraduate degrees, major companies or investment institutions have already offered them high annual salaries of 2 million yuan, 5 million yuan, or 1 million US dollars. However, when discussing salaries of several million yuan, the young researcher sipping marshmallow hot cocoa spoke in a flat tone, as if discussing last semester's class schedule.

"Ah, I don't really care, an extra one or two million doesn't matter much." Another young researcher had a similar thought, "Since I'm going to start a business anyway, I won't be earning a salary for many years." Some major companies and investment institutions also wanted to poach him.

The large model industry has mass-produced hundreds or thousands of young elites with annual salaries in the millions. Major companies have broken past restrictions on age, rank, and experience to recruit young talent with high pay.

Several headhunters and HR professionals said that the annual salary for fresh graduates who are from top universities, have interned in core large model teams at major companies, have top journal papers in matching directions, and have secured major company top talent programs is basically above 1.5 million yuan. A person involved in Seed recruitment said that in 2024, the annual salary for TopSeed campus hires was about 1.5 million yuan, which rose to 3-5 million yuan in 2025, and in 2026, campus hires for core positions could be offered 6 million yuan, with some able to get even more.

Before even graduating, these talents are locked in early—starting at 2,000 yuan, with daily rates exceeding 5,500 yuan at the highest. Someone received a Meta internship offer with a monthly salary of 20,000 US dollars, including room and board. In most industries, where an internship daily rate of 200 yuan is considered good, these figures defy common sense, and people hearing them often need to double-check, "Is that daily or monthly?" "Is that in RMB or US dollars?"

According to industry statistics, the average monthly salary for a delivery driver in Beijing in the first quarter of 2026 was just over 10,000 yuan. An intern earning 5,500 yuan daily is equivalent to 10 delivery drivers. An AI researcher with an annual salary of 3 million yuan earns in one year what a 2025 graduate with a bachelor's degree would earn working diligently for 39 years—provided the latter manages to avoid unemployment.

Even in internet giants known for high salaries, reaching an annual salary of 3 million yuan typically requires a master's degree, 8 to 12 years of continuous work, at least 3 promotion reviews where you rank in the top 30% each time, and being in a core business or catching a period of rapid growth, just to reach levels like ByteDance 3-2, Alibaba P9, or Tencent T11 or above before age 40. By then, you would already be managing a team of dozens and have some renown in the industry.

Yet today, a 22-year-old AI researcher just out of undergrad, who has never managed anyone, made business decisions, or gone through a single performance cycle, receives the same income.

Moreover, they are incredibly young. "Someone born in 1998 is already considered a 'mid-level veteran' in a foundation model team." An intern in a major company's large model team was a bit dejected that he was older than most other interns at the company. Once, working late into the night, he looked up and saw an intern who was "much younger," "literally bouncing around while writing code," he emphasized, repeating, "bouncing around in the literal sense."

The relatively younger ones are just 17—major companies are increasingly setting no age limits, so it's hard to say who is the youngest. She was proactively contacted by a major company's HR, and while preparing for her high school final exams, she interned in a large model team, celebrating Children's Day at her workstation.

"Doing a PhD is such a waste of time!" A young researcher wanted to persuade his friends in Tsinghua's "Yao Class," "Why should the smartest brains learn so slowly?" He gave an example of a 19-year-old Stanford student who left school before finishing sophomore year and quickly raised 4.5 million US dollars in funding for his AI startup, "The worst-case scenario is just going back to Stanford."

A recruiter once persuaded three or four PhD students to drop out and switch to full-time positions, offering highly tempting ranks and salaries. "If studying is to find a good job, you already have one now. And it might not be available in two years." So several young people chose to drop out midway, leaping to catch the AI train.

The founder of an AI company had an even more radical idea. He planned to have his child, who is in the first year of high school, take a leave of absence to work while studying, "How could he possibly learn more at school than he could here with me?"

Global investment firm Antler, after surveying over 3,500 unicorn entrepreneurs, found that in 2024, the average age of global AI unicorn founders was 29, whereas in 2020, most were 40. This number is likely to continue dropping—AI enables these sufficiently smart young people to potentially find higher-paying jobs or push their net worth to hundreds of millions of dollars.

AI Native: Youth is more valuable than experience

Senior executives at internet companies are the elite few at the top, managing technical teams of hundreds or having made achievements in certain businesses, with high ranks, good reputations, and stable positions, allowing them to stay far from the "curse of 35."

Now, past experience has become obsolete. A person formerly at ByteDance Seed said that when ByteDance first invested in large models, it continued its practice of having "big brothers" who had achieved success in business take charge of new ventures. Such leaders were changed two or three times, each bringing their own core researchers, but the results fell short of expectations. Later, the younger Zhou Chang joined and rapidly drove improvements in multimodal capabilities.

"This made us realize our previous talent strategy was wrong," he said.

In terms of resources, DeepSeek is no match for major companies that invest hundreds of billions. Its number of employees is less than 1/10 of a major company's, average working hours are only half, it had never taken any investment before, yet it entered the global first tier of large models earlier than China's top internet companies. We previously reviewed the publicly available 84 resumes among the 172 researchers who participated in DeepSeek's three generations of models; over 70% of them were under 30 years old.

One conclusion ByteDance reached after studying the three "dark horse" companies OpenAI, Anthropic, and DeepSeek was that in the AI field, what truly determines the progress of a business is the key researcher; past management experience and business achievements are not that important. A "big brother" might not necessarily lead researchers poorly, but certainly won't be better than letting researchers directly decide what to do. It's better to let smart young technical talents lead the team.

A person familiar with the matter said that to build the Seed team, ByteDance transferred a TikTok growth product leader to head Seed recruitment. The recruitment logic only looks at how much money is invested and what the output is. The same applies to hiring: it depends on how much you pay him and how much gain he can bring to the company; past rank and salary are meaningless. "Originally, people rated 3-1 were mostly master's graduates with about 5 years of work experience. Today, campus hires can also get the same or even higher ranks."

The new rule has become: the more AI Native you are, the more opportunities you have.

Several researchers tried to explain this concept that has become popular in major company job postings, financing plans, and founder speeches. One said, "The thinking mode is completely aligned with the input and output of large models; you ask AI first when encountering problems, and you know what the next question should be." Another used an analogy: "Why do elderly people need to learn to use smartphones, but kids don't? Because kids understand what happens when they tap the screen. It's the same with large models."

An AI-focused investor answered more simply, "The younger, the better." They are all post-2000s.

From 2022, when OpenAI made large language models mainstream, to models now possessing multimodal, deep reasoning, and programming capabilities, the industry seems to produce new technologies at almost regular intervals.

It's only been four years. Someone who chose the hot direction of "computer vision" for their PhD found the landscape had changed before they even graduated. If they couldn't switch directions fast enough, they too became part of the "previous generation" of AI people.

Beyond four years, the longer you work, the more passive you become. An HR at a large model company said that in 2024, when they were hiring for AIGC text-to-image and video generation positions, they habitually looked for people with visual algorithm experience. They quickly found that those hired also had inertia, first using previously validated technical approaches to solve problems, and if the results were slightly better, they'd just use them. But fresh graduates and more "AI Native" people wouldn't copy past assignments. After changing personnel, the results improved several times over.

"Someone with five or six years of work experience might be able to transition quickly, but why should the company gamble? There are younger ones anyway." After over a dozen candidate resumes were rejected, a headhunter working with a large model company grasped the unspoken rule: "33 is probably the upper age limit."

Headhunters have some screening tricks. If a candidate asks how the company's revenue is—immediately identified as not AI Native enough. Most AI companies aren't making money yet; they care more about computing power, models, and data. Revenue is seen as a financial metric of the previous generation of companies.

"'Genius' managers only want to recruit their own kind. Would a 30-year-old tech lead want to hire someone older and less technically skilled?" a headhunter who has worked with ByteDance asked rhetorically.

She quickly listed several examples: Zhou Chang, who bolstered ByteDance's multimodal capabilities, is in his 30s; Yang Zhilin was also just 30 when he founded Kimi; Lin Junyang, former head of Alibaba's Qwen large model, was born in 1993; Luo Fuli, head of Xiaomi's MiMo large model, was born in 1995; Yao Shunyu, head of Tencent's Hunyuan large language model department, was born in 1998.

Moreover, most young people can work more overtime. A 21-year-old AI intern mostly works from 11 a.m. to past 1 a.m., taking a break in between to eat and walk around to clear his head, and on weekends he also "works a bit, plays a bit." "This has nothing to do with the company; it's my own requirement for myself," he added, "otherwise it's hard to stand out among peers." Another 22-year-old AI researcher didn't find this special; he sometimes works through the night from 9 p.m. to noon the next day, citing being more "immersed." They are still far from the responsibilities and concerns of caring for a family.

Entering high schools, chartering cruise ships, finding younger people

Large model companies have achieved results using young people, and this realization quickly spread—for a company to become AI-driven, it must first become younger. Besides AI researchers, product, design, publicity, and HR also need more young people.

Li Auto announced that 2026 is the last window of opportunity to sprint toward becoming a top AI company. Founder Li Xiang said on his social media this year that without sufficiently deep training and learning, most people with ten years of work experience perform significantly worse than those with one year of experience, and the gap with those top-tier 90th-percentile campus hires is at least tenfold, akin to "ignoring gold and instead opening mystery boxes from ore to refine gold."

In March this year, Geely Holding Group and Xinwei Technology announced a talent program for targeted training of high school students, to build a talent reserve for Geely Intelligent and other businesses.

Recruiting young people isn't just about telling a story of corporate transformation; there are practical work needs. An AI-transforming payment company said they basically only consider candidates born after 1998 for media positions, because active tech KOLs are getting younger and require equally young people to communicate with them. At venture capital firms, those young investors can better connect with entrepreneurs.

Ultimately, the pressure is closing in on the senior ranks of the internet industry. The AI organizational form recognized today must be sufficiently flat and transparent. Young talents dislike traditional high-pressure management and pyramid hierarchies, believing more in meritocracy.

In June, Alibaba replaced Wuzhao, the former president of DingTalk who had taken over a year to bring back, in just a few days. His successor is Chen Yusen, born in 1992. A former entrepreneurial partner of Wuzhao said that Wuzhao is still the same Wuzhao, wholeheartedly wanting to achieve great things, but "he knows the times have changed, but perhaps he didn't notice that people have changed too, and society has changed."

Everyone wants young people, but the problem is that there are only so many truly smart young people. It's crucial to find and secure these young people before they graduate. Several major company HR professionals said they discovered that if a "young genius" has interned at a major company and had a great experience, the probability of them choosing that company after graduation is extremely high. "Smart people are limited; the essence is to establish a connection with them in advance."

In Denver, USA, on the day of CVPR (IEEE/CVF Conference on Computer Vision and Pattern Recognition), one of the "top three conferences," Nvidia, ByteDance Seed, and Intel hosted dinners inviting young scholars. The next day, it was Tencent Qingyun, Alibaba Star, and MiniMax. Half a month later, in Seoul, South Korea, at another top academic conference, ICML (International Conference on Machine Learning), Alibaba, Kuaishou, and Tencent again chose the same day to host dinners.

Tencent stated in its promotion that at least 12 leaders would attend one of its events this year. Kuaishou chartered a cruise ship on the Han River, customized a maritime fireworks display, and had core business leaders engage in zero-distance dialogue with attendees. Alibaba's dinner was held on the 38th floor of the Grand Hyatt Hotel, where Warren Buffett once gave a speech.

To show sincerity, some companies arrange for department heads, vice presidents, and key interns to connect over coffee, spending an hour or two exchanging views on technology and the industry, and chatting about life goals. It's fine if you can't make it this time — some HR staff will still check in on how you're doing, send small gift boxes for Mid-Autumn Festival or Chinese New Year, and mention you can consider them when it's time for a full-time job. "Other people's salary ceiling is our starting point."

A person familiar with Seed said that around 2026, Seed specifically established a "Student Affairs Department" to screen and lock in interns and fresh graduates. Their database covers virtually all outstanding students and fresh graduates in China, holding lists of students from key universities, key labs, and under key advisors, along with their competition experience and internship history.

In theory, if you are an outstanding student from a top high school with a strong enough track record, Seed's HR might know better than your relatives where you are studying, when you will graduate, and where you have interned.

For high-level competitions, they can sponsor GPUs, tokens, or other resources competition coaches need. Beyond the competition winners list, they can also learn about each participant's specific performance. For example, a participant with a low overall score isn't necessarily weak — maybe one of the three judges gave an especially low score. "A semi-open secret," one HR person said. "If you ask around, other companies know too."

For rival companies, Big Tech HR staff are required to tag relevant teams as thoroughly as possible — including daily work performance, output, contribution within the team, and technical strengths — by asking enough people and verifying evaluations, ultimately checking whether there is a match with their own team's needs. If a particular advisor's students performed exceptionally well in past internships, that advisor's team will also receive extra attention. Most advisors are happy to cooperate with large companies, and some students joke about being "packaged into the factory" with their classmates.

One intern contacted by several large companies said that when choosing an internship, the first thing to look at is the team's reputation — large models or multimodal, pre-training or post-training, Group A or Group B — and to first find out whether you'll be doing "dirty work." Second is the number of GPUs available; without them, it's hard to get things done. Third is the team atmosphere and whether there's a chance to interact directly with top experts. Fourth is money.

Big Tech companies are not short on money. ByteDance set up a special Top Seed talent program for the Seed department. Last year, the average daily internship pay was 2,000 yuan. This year, the Top Seed program was nominally canceled, but the maximum salary has no cap. Tencent's Qingyun Plan covers the entire group, with the most spots in AI teams like the Hunyuan large model team. Internships follow a monthly salary system, ranging from over 20,000 yuan to over 80,000 yuan, and some people get around 110,000 yuan — this is also a competitive tactic. With a daily pay system, "you get paid for each day you work," but with a monthly salary system, you also get income during holidays.

Interns circulate sayings like "If there's Seed, choose Seed" and "If there's Goose (Tencent), choose Goose." If that doesn't fit, there is a series of "Star" programs: Meituan's "Beidou Plan," Alibaba's "Ali Star," Kuaishou's "Kuai Star," and Xiaohongshu's "REDstar."

Job postings are written more earnestly than ever. Beyond salary, they emphasize what the company can offer researchers, such as "lead and own core projects," "uncapped compensation," and "join now to take on key responsibilities earlier." To boost appeal in the talent war, the startup Kimi made a high-profile announcement that it would grant stock options a year in advance to interns who pass its top talent program — Zhipu's stock price rose 20x in less than half a year, making the potential value of those options quite intriguing.

After joining a company, these young people also get far more freedom than ordinary fresh graduates.

Some campus hires who join through top talent programs are managed directly by business heads, giving them room to judge what is worth pursuing — initiating projects around new directions, reporting, and building teams — rather than doing 1% or 1‰ optimizations on existing business. Yao Shunyu would invite Tencent Hunyuan interns to meals and organize regular exchange events. One intern said he felt "the company hopes to cultivate you long-term and expects you to achieve something at Tencent."

Some companies promise candidates they can bring along peers who also received talent program offers, first forming a small core team to explore new directions. One campus hire, after joining, felt the computing power was insufficient, so he wrote the request into his weekly report and copied the group's top leader. Three days later, his department received over ten million yuan in computing resources.

The interest chain behind "youth"

In the investment world, "post-00s" has become an important label for projects.

A 27-year-old researcher who doesn't consider himself young anymore just started a company. To secure an allocation, one investment institution sent a term sheet with the amount left blank, meaning "name your terms" — who knows if the "next OpenAI, Anthropic, or DeepSeek" is among the young people carrying backpacks today? That sounds far more imaginative than a 40-year-old starting a business.

"Finally, it's our turn to enjoy the dividends of the era." An AI entrepreneur born in 2003 finished two years of graduate coursework in half a year and spent the remaining time focused on his startup. The first funding round brought in tens of millions of yuan. His co-founder is two or three years older, and the entire team has over twenty people, with some junior students coming as interns. The company is in the AI community near Tsinghua University — where many similar early-stage teams gather.

"That's not a lot." His senior doctoral brother from the same university raised several hundred million yuan in a few months. Among his classmates, someone pushed through four funding rounds within a month of starting a business, "valuation doubled on the spot." He asked, "Do you know what 'on the spot' means?"

"It means nothing changed. The only difference in the business plan was the amount." Investors still kept coming.

The post-00 founders of one company had just signed a financing agreement when, a few days later, one of the co-founders angrily quit. "This is kids starting a business," an investor said. But what if this company succeeds in the future? Who would care that Mark Zuckerberg wore pajamas and a T-shirt to meet investors?

Cao Xi, once the youngest partner at Sequoia Capital and the investor who backed DeepSeek after founding a new fund, said late last year that it is now the era of post-90s founders. Half a year later, the entrepreneurs he was in contact with were born between 2000 and 2002. "Sometimes, I even think, if only I weren't a post-80s."

Similar to MiraclePlus, which focuses on early-stage financing for young people, some investment institutions are starting to form funds specifically for investing in young people. For example, Yunqi Capital's Y Transformer exclusively invests in founders born after 1998, with a budget of 100 million yuan, planning to invest in about 20-25 projects, only in the first round, with a single check of around $600,000 and a decision cycle of 2-3 weeks.

The unspoken rule in the business world used to be the "old boy's club" — mature tech elites, successful entrepreneurs, and investors managing billions in capital supporting each other, "big brothers helping big brothers," with opportunities, trust, and capital circulating among a small group. Core projects in most fields were held by the "previous generation" of investors. Young people didn't know the key entrepreneurs and had no decision-making power. One post-00 investor said he had to adapt to the "big brothers'" rules — be sharp at toasting at dinner tables, read the room, and beg the seniors to bring him along.

AI has given young investors an opportunity — veteran investors don't quite understand it, and entrepreneurs are mostly young, so the "big brothers" are willing to listen a bit more to the young investment managers under them. The founder of one established investment institution said they would put interns in key roles: "Just as the ceiling of many AI companies depends on the talent and effort of interns, the future of investment institutions may well be determined by interns."

It's not just young investors and entrepreneurs helping each other. AI researchers command high salaries, move quickly, and companies have a strong willingness to hire. One company's strategy is "defensive hiring" — even if there is no existing opening, they can't let a rival company hire the person, so they are very generous. Except for the slightly high hiring bar and the scarcity of available talent, everything else perfectly fits the headhunter's business.

They search and persuade those smart young people like hunters. One headhunter received a request: as long as they could bring in researchers from three specified teams for interviews, regardless of whether it worked out, they would get a 10,000 yuan reward for each person. Another company is willing to pay a 30% headhunting fee for a designated researcher candidate — in other industries, that price is only quoted for recruiting a CEO. "If a person's salary is $1 million, the bonus would be at least 2 million RMB," one headhunter calculated.

AI talent is getting younger. Beyond young people being more AI-native and more "useful," all parties can enjoy the benefits that youth brings. A larger theme is that young people band together, collectively build their voice, and together "fight against the old guard."

Young researchers produce results, prove their ability, enter large companies or start their own, and gain management authority; they trust people their own age or younger even more. Younger researchers and interns have the drive to explore, prove themselves to management, or get spotted by young investors; young investors who back good projects get promoted faster.

"People the same age naturally connect better!" One researcher who spent time in the San Francisco Bay Area — the epicenter of the AI storm — said that there, 20-year-old founders hire 18-year-old employees and get backed by 19-year-old investors. They didn't know each other before, just sent an email: "I'm really interested in your paper, my idea is xxx, let's chat?"

He said some investors in China still follow "that old routine" — handing out business cards first, with a headshot on the left and a list of titles on the right. Young people rarely do that. "What titles do we have?" As long as the ideas are interesting, he doesn't mind meeting new friends through an email. The next moment, "I know a few friends like you, you'll get along," and gradually a network forms. Ideas spread like wildfire, and a few smart young people can form a startup, get funding, and compete with resource-rich large companies.

No one stays young forever

In this extreme atmosphere of chasing youth, a former "Huawei Genius Youth" was hit from all sides. When he graduated with his PhD, the salary for Huawei's Genius Youth program far exceeded that of his peers. Even at a top university, it was an enviable destination. Two or three years later, his junior schoolmates' salaries completely surpassed what he had imagined for fresh graduates — ByteDance began recruiting foundational model R&D talent with high pay, no cap on headcount, and often offered double the salary increase.

Another year later, when he started his own business, Tencent and Alibaba also joined the talent war, and the compensation expectations for top campus hires were "shockingly high." He could only play the emotional card, saying he was more reliable and offering more stock options, to recruit from his alma mater. When seeking funding, the "Huawei Genius Youth" title still worked, but it wasn't as attractive as a post-00 star entrepreneur.

Young people come in wave after wave; there is no youngest, only younger. Competition is fiercer than before. One AI industry insider watched the number of top academic paper submissions in the field go from around one or two thousand around 2020 to seventy or eighty thousand today. A master's student used to be considered good if they published two top-tier conference papers; now that standard has doubled, and doubled again.

One AI researcher posted interview tips for Big Tech top talent programs on a platform and created an exchange group, requiring relevant internship experience to join. The 500-person group filled up in two days. They chat about interview experiences and the real situation inside teams. Many Big Tech HR staff follow his account "Random Field" to gather information on some interns and fresh graduates.

The unwritten rule is that to get into a top talent program, you need a good internship. To find a good internship, you need to have already had a good internship. "So what about the first good internship? Rely on senior schoolmates or strong internal referrals from advisors." One post-00 intern said with a serious expression, "No one to refer you? Then you're betting on luck."

Another candidate who received a top talent program offer judged that "the circle for foundation models has already closed." Interns from a few large model companies circulate among themselves, and after converting to full-time, they recommend their juniors. "People inside don't flow out, and people outside can't get in."

"Many facts are better left unknown; telling them is cruel." A person familiar with AI industry hiring hesitated. "In the past, an ordinary college graduate earned 100,000 a year, and a Tsinghua or Peking University graduate earned 1 million a year. People could accept a tenfold gap. But now a Tsinghua or Peking University graduate might earn 5 million a year, while an ordinary college graduate can't even earn 50,000. The gap has stretched to 100 times. Isn't that cruel?"

One post-00 AI researcher said he feels lucky. "This era's reward for the extraordinary has never been so generous" — the AI industry's generosity toward young people easily makes people notice only the first half of that sentence, while ignoring the second half — "but the punishment for the ordinary has never been so severe."

That "Huawei Genius Youth" can at least start a business. Most of his peers went from undergraduate to PhD, passed at least five rounds of interviews, beat out other candidates, and entered Big Tech internet companies around 2020, becoming elites in a high-paying industry. The "35-year-old" age anxiety certainly existed, but they always thought about continuously refining their skills, pushing themselves to just run faster than the 10% of colleagues facing elimination.

Then AI arrived. Front-end developers immediately became "redundant" in the eyes of companies. For other software programmers, it's only a matter of time — most Big Tech programmers live in constant fear, distilling themselves harder than their colleagues, striving to eliminate their colleagues first, only to be eliminated by AI in the end.

Before the second half of 2025, a programmer over 30 working at a major tech company had never doubted that he was "getting old." He pursued a PhD in the United States, smoothly landed a job at a major tech firm, and had always kept an eye on new technological shifts. But one day, he suddenly felt that updates and information about large models were erupting like an unstoppable faucet, and his past experience had turned into a "negative asset."

Immense anxiety washed over him. "In the past, one person couldn't read 200 articles a day. Now you can collaborate with AI to read 300, 500, or even 1,000 articles." The problem was, "What if I miss something?" Every night before bed, he would assign tasks to the AI, trying to dispel some of his unease.

Hearing this, a post-00s AI researcher immediately asked, puzzled, "What else would you expect? It's like cars replacing horse-drawn carriages. Advanced productive forces are bound to replace backward ones."

A few hours later, another researcher who didn't know him used the exact same analogy: "Why don't they switch earlier?"

"But someone driving a carriage might find it very hard to learn to drive a car." "Well, that's how society progresses." He added, "Four words: their vision is too narrow."

The programmer in his 30s fell silent after hearing this recounted. After hesitating for a long time, he spoke: "We all know no one can stop technology. Plugging your ears while stealing a bell is foolish; you just have to keep up. But it's hard to explain to them that change isn't that easy." He left that major tech company, wanting to explore new technologies in a different way.

A few days later, he sent a message saying he had once again felt the brutal confidence of the young. Chen Yusen, born in 1992, succeeded Wuzhao—who had interned at Alibaba back in 1999—as the new CEO of DingTalk. This event has many complex dimensions, but the summary from the young people around him was: "Remove the 'old guard,' bring in the young, and everything will get better." He seemed to not belong to that jubilant new world.