Pang Dong Lai, a popular Chinese retailer, is preparing to close one of its older stores when its leases expire. Online, the story has been framed in a much simpler way: greedy landlords raised the rent, and the company refused to bow down or negotiate. It just walked away.

     A similar story has circulated about Tencent leaving the Kexing Science Park in Shenzhen. In that version, landlords get greedy, companies stand firm, and everyone watching gets the satisfaction of seeing someone finally say, “Enough.”

       But once you set the emotion aside, the situation looks more complicated.

1. This Is Not Just a Story About Higher Rent

       The older Pang Dong Lai store sits in a building divided among dozens of individual owners. The company had to negotiate separate leases with separate landlords instead of dealing with one property owner or management company.

       That setup creates obvious problems. An owner with a storefront near the main entrance may prefer a short lease and demand more at renewal. An owner on an upper floor or in a less desirable corner may accept very different terms. Even if the retailer wants one unified agreement, not every owner has a reason to go along.

       The most widely shared claim is that annual rent jumped from 8 million yuan to 18 million or even 24 million yuan. According to the original discussion, a rent dispute of that scale did happen at another Pang Dong Lai location years earlier. It may not have been the direct cause of this store’s closure.

       Combining numbers, events, and locations makes for a stronger viral story. It also makes the facts harder to sort out.

2. The Old Store Has Problems Rent Alone Cannot Fix

        This store has been operating for more than 20 years. It covers about 23,000 square meters, and it faces a more basic problem: it is no longer built for the traffic it attracts.

       The facilities are old. The layout is tight. There is no underground parking. Customers and cars now overwhelm a space designed for a different era.

       A successful store can still be held back by its building. If getting there means sitting in traffic and the inside layout cannot be meaningfully improved, strong sales do not solve everything.

       Major renovation would also be difficult. With dozens of owners involved, even basic changes require negotiation after negotiation. Adding parking, redesigning traffic flow, or rebuilding the property would be far harder than simply updating the décor.

       So closing the old store may not be a dramatic act of defiance. It may be a business decision: instead of endlessly patching a building that cannot be fully modernized, put resources into a space designed for the future.

3. The Bigger Shift Is From Renting Space to Building It

       Pang Dong Lai is building a new project called Dream City. It is planned to cover about 580,000 square meters, with an investment of 6.5 billion yuan. The company says it will use its own funds and plans to open in 2029.

       Tencent is making a similar move. Kexing Science Park had long struggled with congestion and pressure on its surrounding infrastructure. Tencent’s new Penguin Island campus began construction in 2021, with an investment of more than 30 billion yuan. By the end of June this year, about 28,000 employees had moved in. When the second phase is complete in 2028, the campus is expected to hold 80,000 to 100,000 people.

       Both companies are making the same basic choice: moving from rented space to space they can own and plan themselves.

       That is expensive. But it gives a company more control over parking, transportation, office layout, future expansion, and supporting services. It also reduces the time and uncertainty involved in negotiating with many landlords every time a lease comes up.

4. A Company’s Value Does Not Stop at Its Front Door

       Large stores and corporate campuses bring customers, employees, restaurants, housing demand, and other services. As a result, they can also increase nearby property values.

       That is one reason companies care so much about land and self-built campuses. They are not only trying to lower rent. They want to retain more of the long-term value created by their brand, foot traffic, and business activity.

       Warehouse clubs such as Sam’s Club offer a familiar example. Some locations are built in areas that are not yet fully developed. Once the store and its parking infrastructure bring in regular traffic, nearby land and housing can become more valuable.

       In the best case, this is not a zero-sum game. Developers, retailers, local businesses, and customers can all benefit from a new commercial center.

5. Why the “Walk Away” Version Spreads So Easily

       Because it gives people an emotional release.

        Many people have jobs, families, bills, and responsibilities that make it hard to simply walk away from an unfair situation. They may feel frustrated, but they cannot always afford to quit, move, or start over.

        That is why a story about a company saying, “I’m done,” is so appealing. The landlord becomes the obstacle. The business owner becomes the person who finally pushes back. It is simple, satisfying, and made for social media.

       The problem is that the more satisfying the story becomes, the more likely it is to leave out the difficult parts: Why did the old building stop working? Why is ownership so fragmented? Why were those leases signed in the first place? What risks did each side accept when they did?

6. Turning Landlords Into Villains Does Not Solve the Real Problem

       If some owners ask for higher rent and the tenant refuses, that is a normal commercial conflict. The company can leave. The owners can risk vacancies. Whether either side made the right choice will be decided by the market.

       The more useful questions are different. Why can a building that once worked become so hard to upgrade? Why does fragmented ownership make modernization nearly impossible? Why does a company that creates enormous traffic still have to spend so much energy on short-term lease negotiations?

      The Pang Dong Lai story matters for more than rent or corporate bravado. It shows what happens when an old space can no longer support a growing business. Sometimes leaving is not about winning an argument. It is simply the next practical step.

      On August 2, Lenny's Podcast — basically required listening for product people in Silicon Valley — dropped an episode with a spicy title: "This CPO regrets that the product manager role exists."

      The guest, Verrilli, is no outsider. He's the Chief Product Officer at Whatnot, previously CPO at Twitch, and before that, director of product growth at Twitter. A guy who climbed the product ladder all the way to the top, turned around, and said: this job should never have existed.

      And his company makes it hard to dismiss as venting. Whatnot is a livestream shopping platform — hosts run live auctions; it started with trading cards and collectibles, now it sells everything. In 2025 it did $8 billion in sales at an $11.5 billion valuation — with just 20 product managers out of 1,200 employees. Silicon Valley's rule of thumb is one PM for every five engineers. Over the past two years, 31,832 people applied for a PM job at Whatnot. They hired one.

      This isn't a dying company cutting costs. It's one of the fastest-moving companies around saying: I don't need many product managers — and I'm still outpacing you.

1. Why he hates the role

      Verrilli gives three reasons, each sharper than the last.

      First, the role rewards the wrong skills. What's valued most isn't understanding technology or customers — it's politics: driving alignment, building relationships, telling good stories upward. People do politics and call it product management. He calls it an anti-pattern.

      Second, it's not the people — it's the system. He points to Twitter's endless "alignment meetings" and offers the most quotable line of the whole interview: your system breeds systems. Build an organization that rewards performative alignment, and it will grow you a generation of PMs whose profession is alignment. These people aren't bad; the org simply pays them to that standard.

      Third, PMs turn engineers and designers into children. They're perfectly capable of making good calls — they just never have to, because a PM is always there to babysit. Junior PMs have gone from "CEO of the product" to "button babysitters."

      I've lived this myself. At Cheetah Mobile — a Chinese app company whose founder, Fu Sheng, branded himself "China's number one product manager" — product management was the only path to promotion. And how do you get promoted? By grabbing authority: "No, you don't understand product. I'll tell you how it's done." Over time, the whole system becomes a political system.

2. He's not against alignment — he's against alignment as a career

      One thing needs to be clear, or you'll misread him: he's not advocating chaos. At Whatnot, you get autonomy over execution; nobody gets autonomy over strategy. His own words: "Without alignment, autonomy is wasted."

      What he opposes is a class of people who coordinate for a living. What he wants is a small number of senior, hands-on PMs who dare to make the call — because in a big, inertial organization, going with the flow is the easy path, and being the decision-maker is exactly what you hire a PM to do.

3. The job was born political — in 1931

      On May 13, 1931, a P&G advertising manager named Neil McElroy wrote an 800-word memo. He was pushing a soap called Camay, and his biggest rival wasn't on the market — it was inside his own company. Ivory, P&G's flagship, held all the resources, and Camay got blocked by its own colleagues at every step.

      The memo looked like a staffing request — "I'm drowning, give me two more people" — but what it really proposed was this: every brand needs one person who owns it end to end, watching sales, running product, ads, and promotions, and getting out into the market to meet real customers. His boss read it and reorganized all of P&G around brands. Every P&G CEO since has come up through brand management. McElroy himself became president in 1948, and later Eisenhower's Secretary of Defense.

      See the point? This role was built from day one to fight internal wars — to coordinate resources inside a company. The politics and alignment Verrilli rails against aren't a corruption of the job. They're its birthmark.

4. The internet grew the role a second leg

      So why does everyone today think of PMs as "the person who defines the product"?

      P&G's brand managers defined products too: analyze competitors, claim a lane — say, "smoothness" — then get packaging from design, the formula from the lab, and airtime from advertising. That's how the shampoo brand Rejoice was born. But what they delivered was a brand, not a feature. Today's internet PMs ship apps and features, lead their own engineers and designers, and decide "who calls the shots" on their small team. The classic case in China is Tencent — its early nickname among users was "the damn penguin," because it was so good at copying. And "copying well" is exactly what tests a PM: tear a rival's product apart, understand it completely, then redefine it with your team.

       So the job has always walked on two legs: one is coordination and politics, the other is understanding and judgment. In P&G's era, the first leg was stronger. Internet companies emphasized the second. But the first leg never went away — the bigger the company, the faster it grows back.

5. AI is taking exactly that first leg

      For a while, the trendy way to use AI was role-play: "You're the designer, you're the tester" — and let several agents discuss like a human team. People who tested it found the results were bad, because it ports humanity's bureaucracy onto AI. Humans need meetings and handoff docs because we can only hold so much information at once. AI just calls all that "context" — it can absorb a million tokens (roughly hundreds of thousands of words) in one go. No relay required.

      So frontier labs like Anthropic changed course: one unified agent that takes the task, breaks it down itself, delegates to sub-agents, and delivers the summary.

      Notice — "break down, coordinate, summarize" is exactly the PM's daily grind. The most toxic half of the role is precisely the half AI is best at absorbing. The other half? AI can't take it.

6. What's left for humans

      Engineers: from writing code to drawing boundaries. With vibe coding — describing what you want in plain English and letting AI write it — building real systems actually demands more: you don't have to write memory management by hand, but you must understand it, and you must draw boundaries. Tools like Claude Code and Codex default to "band-aids": the smallest possible fix, because they don't know where their boundaries are. There's a sci-fi story about a computer that could answer anything; asked "what should humanity do?", it thought for ages and answered "42." We don't want that answer — so humans draw the boundaries.

      Designers: from hands to eyes. AI can crank out a hundred drafts in minutes. Who picks? Still the designer — who then combines and refines. The skills that matter now: understanding what the client actually wants; taste — it used to be about the hand (can you draw it), now it's about the eye (can you pick it); plus the communication skills to explain the choice.

      Product managers: keep the judgment, add the labeling. Understanding business, customers, and data, then making the call — that leg stays. The new job is data labeling: AI can't tell which market feedback is a good signal and which is noise. PMs turn real-world data into signals AI can learn from, feed them back in, and iterate fast alongside AI.

7. What really gets rewritten: "the product" itself

      Push one step further: what gets disrupted may not be any job, but "the product" itself. We're used to products having boundaries: separate Android and iOS versions, compatibility headaches, app store rules. But what we actually want is the service and the result, not the product-shaped shell — and the productivity wasted maintaining those boundaries often exceeds what goes into the result.

      When we built Clean Master, a phone-cleaning app, fewer than 10 people actually worked on "cleaning." The product team had two to three hundred. What did the rest do? Maintained boundaries — and monetized, by showing users ads. It's like buying a bottle of Rejoice: you want softer hair, but an army of people is debating whether the bottle should be green. In the AI era, product boundaries may dissolve — or get redrawn entirely.

8. Wrapping up

      So in the age of AI, what actually gets replaced?

      My answer: the defaults. The default of one PM for every five or six engineers. The default that meetings are the job. The default that products must have today's boundaries. A role invented in 1931 has grown parts that are actively harmful to organizations — and those parts are exactly what AI absorbs best.

      The question worth asking isn't "will my job disappear?" It's: strip away the job title — what service and value do I actually deliver? Or more bluntly: how much of my day produces results, and how much just maintains boundaries? I'd love to hear your answer.

      In these two years, the world was obsessed with one dramatic question: Will AI hurt humanity? Will it replace us? Will it rule us? Elon Musk, Sam Altman, Dario Amodei — everyone was shouting.

      But while the debate raged, China quietly built an advantage in a different contest — the race over algorithms. And it did so in a very Chinese way: not by inventing the best chips or the strongest models, but by creating the world’s most intense competitive arena.

1. China’s internet ecosystem

      People call it the “gu jar.” In an old legend from southwest China, you throw various poisonous insects — centipedes, scorpions, and the like — into a jar. They fight and bite until only the strongest, most toxic one remains: the gu king.

      China’s internet ecosystem works a bit like that jar.

      Inside go hundreds of millions of atomized individuals and countless small merchants. A group of highly compliant platforms runs the jar. Fierce algorithms battle inside. And sitting on the lid is the “jar keeper” — the government. It doesn’t lift the lid, but it controls the temperature and sets the rules that decide who ultimately wins.

      After brutal elimination, the survivors that crawled out include global powerhouses like TikTok, Temu (Pinduoduo’s overseas version), and Shein — plus rising stars like Meituan and Didi that are now expanding worldwide.

2. How does the government manage this jar?

       In February 2025, China’s State Administration for Market Regulation issued the Anti-Monopoly Compliance Guidelines for Internet Platforms. It was followed by waves of meetings with companies, clearly defining eight types of new monopoly risks.

      In plain terms: the insects in the jar were told — these eight ways of “biting” are not allowed.

The eight categories roughly cover:

• Algorithm collusion between platforms:
  Platforms share data and coordinate against users. Search for something on Taobao, and suddenly Douyin recommendations become eerily targeted.
• Helping merchants form price-fixing agreements:
  Platforms assist sellers in setting unified prices or price ranges.
• Unfair high pricing by platforms:
  Using dominant position to raise commission rates that merchants can’t escape (often discussed in the context of Meituan).
• Selling below cost:
  Aggressive subsidy wars, such as Alibaba’s zero-yuan purchase campaigns against Meituan.
• Blocking and shielding:
  Preventing mentions of competitors (e.g., saying “Dou something Yin” instead of Douyin on WeChat).
• Exclusive dealing (“choose one or the other”):
  Merchants can only operate on one platform.
• “Lowest price across the web” (most-favored-nation treatment):
   Influencers sign agreements requiring the absolute lowest price.
• Differential treatment by platforms:
  Big-data price discrimination — new users get better deals than returning ones.

      These rules aim to stop algorithms from being weaponized for monopoly power.

3. Consumers can fight back too — the “add to cart and wait” trick

      Interestingly, consumers sometimes turn the tables. The simplest move: see something you like, add it to your cart, but don’t check out immediately.

      Why does it work? Once the item is in your cart, the algorithm shifts into full persuasion mode — flooding you with coupons, reminders, bundle suggestions, and loyalty points. The goal is simple: get you to complete the purchase.

      Algorithms operate in stages. First they figure out who you are and what you like. Then they bombard you with content. Once you engage, they double down. The moment you add to cart, the mission changes to “close the deal.”

      Platforms would rather give bigger discounts and more coupons than risk an uncompleted transaction. Their core metric is completed orders, not maximizing profit per order.

4. Why can only China grow these kinds of “monsters”?

Three key conditions make this system especially effective in China:

i. Increasing social atomization
      China now has around 320 million flexibly employed people — nearly half of its 700+ million labor force. Many lack stable employers and work in highly individualized, gig-style arrangements. This gives algorithm platforms a massive pool of atomized users and workers. The West hasn’t reached this stage yet, largely due to unions, industry associations, and legal protections. But in the AI era, societies worldwide are likely heading in this direction — exactly the environment these platforms are built to thrive in.

ii. Few traditional brakes or constraints
      Western platforms face unions, lawsuits, and public scrutiny that limit how aggressively they can compete. Chinese platforms operate with fewer external restraints because the system favors atomization for social stability reasons.

iii. Highly concentrated government power
      Western governments that want to regulate algorithms often hit limits from checks and balances. China’s government can set rules, summon companies, and adjust enforcement granularity more directly. This gives the “jar keeper” strong control over the arena.

      Inside this jar, algorithms don’t just target consumers — they also manage delivery riders and small merchants (tiny restaurants, shops, etc.). The government uses frequent guidelines and meetings, mainly targeting big platforms (because they’re large enough and responsive), to keep the whole system stable. High-profile actions, like pulling Didi back from the stock market, serve as strong signals.

5. How powerful are these “monsters” once they go global?

       Once they leave the jar, these companies show remarkable strength. TikTok dominates global short video. Temu disrupts Western e-commerce with ultra-low prices. Shein has taken fast fashion worldwide.

      Meituan and Didi are expanding into Hong Kong, Southeast Asia, Brazil, and the Middle East.

      Local traditional businesses struggle to compete. These companies were forged in China’s most brutal market conditions: they understand human psychology deeply, squeeze efficiency relentlessly, and know exactly how to dance on the edge of rules.

      They often expand using a “scout” approach — small overseas-registered teams or entities test the waters while parent companies provide resources and subsidies. Once they scale, they become hard to dislodge. TikTok, for example, set up a U.S. data-management company, but the core algorithm and operations remain under ByteDance control.

6. The cost — and the open question

      This gu-jar system is undeniably powerful. It has allowed China to lead in adapting algorithms to an atomized society and has produced a batch of globally competitive platforms.

      Yet the jar is fed by hundreds of millions of ordinary people who have been repeatedly “bitten”: delivery workers facing tighter time windows and lower pay, small merchants operating on razor-thin margins, and consumers navigating information asymmetry and algorithmic nudges.

      When a society is largely connected and managed through algorithms, and the main restraining force rests with the government alone, life inside the jar can feel precarious.

      The AI era is only beginning. Atomization will deepen, algorithms will grow stronger. The surviving “monsters” will only become more potent.

      The real question is this: Besides the jar keeper’s hand on the lid, can the people inside also hold onto a rope of their own — some form of meaningful counterbalance?

      There is no clear answer yet. But for anyone who has been shaped by these algorithms — and who has shaped others through them — it’s a question worth keeping in mind.