The Economics of "Ploughing" (or "Further Exploitation"): The Hidden Symbiotic Chain Between Project Teams, VCs, and Studios

Author: danny

Around the winter of 2020, the project teams' goals shifted from "creating value and serving users" to "listing on exchanges and serving studios well." The core driving force behind this phenomenon lies in the contradiction between exchanges' rigid demand for data and the cold start of early-stage projects. Due to the lack of real initial users and data, but the exchanges' need for such data, project teams were forced to "collude" with studios to create a false sense of prosperity through inflated trading volumes to meet market expectations.

This model leads project teams to directly "start up for exchanges" and "start up for airdrop hunters." Against this backdrop, the industry experiences a "bad money drives out good" phenomenon, where fraudulent, arbitrage-driven interactions (bad money) crowd out network resources, diluting rewards and increasing usage costs, thereby driving out genuine, utility-oriented users (good money).

What began as a marketing campaign to attract new users—the "airdrop" mechanism—has completely lost its original purpose and has become a lifeline for studios and bots. Project teams and exchanges are indulging in this data-driven facade built on scripts, leading not only to a massive waste of resources but also fundamentally misleading the industry's development direction.

This article aims to discuss the root causes, mechanisms, and impact of this phenomenon on the future of the industry. We will explore how leading exchanges such as Binance and OKX have inadvertently become the "guide" for this distorted incentive mechanism through their listing standards; and analyze how venture capital institutions, through the design of "high FDV, low circulation" token economics, have formed a hidden symbiotic relationship with "profit-seeking studios" to jointly complete this grand drama of false prosperity.

I. The Incentive Structure of a “False” Economy: From Value Creation to Alienation Driven Only by Going Public

The proliferation of cryptocurrency arbitrage studios is not a random disorder, but a rational economic response to the established incentive structure of the current cryptocurrency market. To understand why project teams would, or even "tacitly approve" of the existence of these studios, we must first analyze the survival rules set by the "gatekeepers" who hold the power of life and death in the industry—CEXs, VCs, and KOLs.

1.1 The Gatekeeper Effect of Exchanges: Data as an Entry Ticket

In the current token economic model, for the vast majority of infrastructure and middleware protocols, achieving a "grand slam" listing on top-tier exchanges (such as Binance, OKX, and Coinbase) is the definition of project success. This is not only a necessary liquidity event for early investors to exit, but also a sign that the project has gained mainstream market recognition. However, the listing standards of exchanges have objectively created a demand for fabricated data.

Exchanges rely on quantitative metrics to scrutinize listing applicants. While Binance, the largest exchange by market share, publicly emphasizes "strong community support" and a "sustainable business model" in its listing criteria, in practice, trading volume, daily active addresses, on-chain transaction volume, and TVL (Total Value Limit) are often given high weight. OKX similarly explicitly states that, in addition to technical aspects, they pay close attention to "adoption rate metrics" and "competitive market position."

This mechanism creates a classic "cold start paradox": a new Layer 2 or DeFi protocol needs real users to qualify for listing, but it's difficult to attract real users before the liquidity and token incentives expected from listing. Luckin Studio fills this gap by offering a "growth-as-a-service" solution. Through automated scripts, the studio can generate hundreds of thousands of daily active addresses and millions of transactions in a short time, charting a perfect growth curve to meet the data requirements of exchange due diligence teams.

This pressure is also reflected in the rumors surrounding so-called "listing fees." While leading exchanges like Binance frequently deny charging exorbitant listing fees and emphasize transparency, in reality, projects often need to commit to a certain trading volume or liquidity, or provide a significant amount of tokens as part of their marketing budget. If a project lacks sufficient organic traffic, it must rely on market makers and studios to maintain this false sense of prosperity to avoid being delisted or placed on a watch list by exchanges.

1.2 The Pressure Cooker of VC: Vanity Metrics and Exit Liquidity

Venture capital (VC) has played a pivotal role in this ecosystem. Over past cycles, billions of dollars have poured into the infrastructure sector. The business model of VCs dictates that they must seek exit strategies. A standard lifecycle for a crypto project includes seed rounds, private placements, and ultimately, TGE and an IPO.

During the TGE (Transfer-Oriented Fund) phase, project valuation is highly correlated with market buzz and discussion. Because the crypto industry lacks traditional P/E or discounted cash flow models, valuations often rely on proxy metrics.

• The number of active addresses is directly interpreted as the "number of users".
• The number of transactions is interpreted as a measure of "demand for block space" and "user activity."
• TVL is interpreted as "trusted capital" or "cold start-up capital".

Fueled by industry cleansing and previous get-rich-quick myths, the crypto sector has attracted many short-sighted speculators who prioritize "soil metrics" over intrinsic value. VCs, knowing they are competing with retail investors for limited liquidity, will pressure their portfolio companies to maximize these metrics before TGE.

This creates a serious moral hazard: VCs have an incentive to turn a blind eye to Sybil activities, or even to push them behind the scenes, because it is the data contributed by these studios that supports their high-valuation exits. This explains why you see some TGE projects with nearly a million followers on Twitter, hundreds of millions of interaction addresses, and billions of transactions, etc.

While total registered users or initial transaction volume may seem compelling on the surface, they often lack correlation with the long-term success of a business. However, these metrics are standard requirements and a barrier to entry at the primary market negotiating table. A project with 500,000 “active addresses” (even if 99% are bots) often commands a much higher valuation than one with 500 real high-net-worth users.

1.3 The alienation of marketing activities: from customer acquisition to feeding robots

Airdrops were originally designed as a decentralized marketing tool to distribute tokens to real users and generate network effects. However, under the current incentive structure, the nature of airdrops has undergone a fundamental change.

Project teams discovered that instead of spending budgets educating the market and finding real users (a slow and expensive process), it was more effective to attract studios by hinting at an airdrop. These "points-based" or "task-based" marketing campaigns are essentially a data-buying transaction (some even call it a future discounted token purchase). The project team pays (or promises to pay) tokens, and the studios deliver on-chain data, gas fees, and transaction fees. In the short term, this transaction is beneficial to both parties: the project team gains impressive data to showcase to exchanges and venture capitalists, while the studios receive the anticipated token rewards.

However, the victims of this collusion are the entire industry's product culture and real users. Because studios only need to meet the minimum interaction threshold (e.g., once a week, for amounts greater than $10), project iterations have begun to optimize these bots and scripted interaction logic, rather than improving the real user experience. This has led to the creation of a large number of "zombie protocols" that are useless except for inflating transaction volumes—because their functions are designed for bots. Come on, nobody would go all the way from chain A to chain B just to swap a $10 token, okay?

II. The Industrialized Operation Mechanism of the Hair-Plucking Studio (Supply-Side Analysis)

The term "Luffing Studio" carries a somewhat grassroots connotation, even containing elements of online mockery, representing a self-deprecating joke within the community. However, in the context of 2024-2025, it refers to a highly specialized, capitalized, and even professionally developed high-tech industry. These entities operate with the efficiency of software companies, utilizing sophisticated tools, algorithms, and infrastructure to maximize the exploration of reward mechanisms.

2.1 Industrial-grade infrastructure and automation

The barrier to entry for Sybil attacks has been significantly lowered, largely thanks to the widespread availability of specialized tools. Fingerprinting browser tools such as AdsPower and Multilogin allow operators to manage thousands of independent browser environments on a single computer. Each environment possesses a unique digital fingerprint (User Agent, Canvas Hash, WebGL data, etc.) and a unique proxy IP address. This renders traditional anti-fraud measures based on Web2 technologies (such as detecting logins from the same device) completely ineffective.

A typical studio operation process includes the following highly industrialized steps:

Identity spoofing and isolation: Use fingerprint browser to isolate the local storage and cookies of thousands of wallets, ensuring that they appear on the front end to be independent users from all over the world with no connection.

Batch Wallet Generation and Management: Addresses are generated in batches using hierarchical deterministic (HD) wallet technology. To circumvent on-chain clustering analysis, the studio uses CEXs that support sub-accounts for fund distribution. Since the hot wallet addresses of CEXs are universal, this severs the correlation of on-chain fund sources, breaking the fund tracking graph commonly used by "witch hunters." (Advanced versions also stagger transfer times, transfer amounts, etc.)

Scripted Interactive Execution: Write Python or JavaScript scripts and combine them with automated testing frameworks such as Selenium or Puppeteer to execute on-chain interactions around the clock. These scripts can not only automate operations such as Swap, Bridge, and Lending, but also introduce random modules to simulate human operation intervals and amount fluctuations to deceive behavioral analysis algorithms.

KYC Supply Chain: For projects attempting to block studios through mandatory KYC (such as CoinList public offerings or verification by certain projects), a mature KYC data supply chain has formed in the underground market. Studios can purchase real identity information and biometric data in bulk from developing countries at extremely low costs, and even use AI technology to completely breach the Proof of Personhood defense through liveness detection.

2.2 "Task Platform": A Training Base and Accomplice in Industrialized Traffic Boosting

Another key development this period is that, in addition to Web3 task platforms such as Galxe, Layer3, Zealy, and Kaito, established wallets and project teams, such as Binance Alpha, various Perp Dex, and emerging L1 tokens, have also joined the ranks. These platforms ostensibly position themselves as tools for educating users or building communities, rewarding users with points or NFTs by issuing "tasks" (e.g., "Cross-chain ETH to Base," "Make a swap on Uniswap").

However, these platforms have become the "training ground" and "task list" for hair-grooming studios.

Layer3 essentially operates a "growth as a service" marketplace. Partners pay Layer3 for traffic, and Layer3 distributes these tasks to users. For studios, Layer3 clearly outlines the interaction paths approved by the project team. Studios only need to write scripts for these specific paths to obtain "officially certified" interaction logs at minimal cost.

Kaito is another marketplace for renting media buys. It's filled with the voices of numerous AI bots, indirectly contributing to the proliferation of AI-generated comments and invalid tweets on Twitter.

Galxe allows projects to create tasks that include on-chain interactions and social media engagement. While Galxe offers some anti-Symania features (such as Galxe Passport), these are often paid premium options, and many projects deliberately avoid enabling strict filtering in order to maximize participation data.

Ironically, these platforms unintentionally (or perhaps intentionally) trained bots. By standardizing complex interactions into a linear "task A + task B = reward," they created a deterministic logic, exactly what scripts excel at. The result was a large number of "mercenary users" who mechanically performed the minimum actions required to earn a reward, ceasing all activity immediately once the task was complete.

2.3 The Economics of Capital Allocation: ROI-Driven Capital Allocation

The essence of a "customer acquisition" studio is a capital allocation strategy. In the studio's books, gas fees, slippage losses, and capital tied up are considered customer acquisition costs. They calculate the return on investment (ROI).

If you spend $100 on gas fees on a cluster of 50 wallets and end up receiving $5,000 worth of airdropped tokens, the ROI is a staggering 4,900%. Such exorbitant profits are historically common.

Starknet Case Study: A typical GitHub developer account can earn approximately 1,800 STRK tokens. At the initial launch, the token price exceeded $2, meaning a single account could earn over $3,600. If a studio used scripts to register and maintain 100 GitHub accounts in bulk, their total earnings would exceed $360,000.

Arbitrum Case Study: Arbitrum's airdrop distributed approximately 12.75% of the total token supply. Even wallets with minimal interaction received thousands of dollars worth of ARB. This massive liquidity injection not only validated the viability of the studio model but also provided them with ample ammunition (capital) to launch larger-scale attacks in the next cycle (such as zkSync, LayerZero, Linea).

This high return creates a positive feedback loop: successful airdrops provide studios with funds to develop more complex scripts, purchase more expensive fingerprint browsers and proxy IPs, thereby gaining a larger share in the next project and further squeezing out the living space of real users.

III. Ruins Beneath the Data: Currency Issuance. People Gone. Buildings Empty.

The consequences of the studio's "victory" are starkly revealed in the dismal performance of the main protocols after the airdrop. This exposes a clear pattern: growth in production -> airdrop snapshot -> retention collapse.

3.1 Starknet: Avalanche of Retention Rates and Extremely High Customer Acquisition Costs

Starknet, a prominent ZK-Rollup network, conducted a large-scale airdrop of STRK tokens in early 2024. Its distribution criteria were quite broad, aiming to reach developers, early adopters, and Ethereum stakers.

This data is astonishing. On-chain analysis after the airdrop revealed that only about 1.1% of the addresses that claimed the airdrop remained active afterward. This means that 98.9% of the winning addresses were mercenaries who immediately ceased contributing to the ecosystem after taking their rewards.

Starknet actually spent approximately $100 million (in token value) to acquire about 500,000 users. However, considering a retention rate of only 1.1%, the cost of acquiring a single retained user skyrocketed to over $1,341. This is a completely unsustainable and disastrous figure for any Web3 protocol or Web2 company.

This selling pressure caused the STRK token price to plummet by 64% after its release. Although the total market capitalization appears to have increased due to the token unlocking plan, the token's purchasing power has shrunk significantly.

Starknet's case provides a textbook example of what not to do: users expected to be "purchased" through airdrops are merely illusions. Studios extract value and move on to the next battleground, leaving the protocol with only inflated historical data and empty block space.

3.2 zkSync Era: The End of an "Era" and the Cliff of Data

zkSync Era's trajectory mirrors that of Starknet. Prior to the airdrop of snapshots, the network's active address count grew exponentially, often surpassing that of the Ethereum mainnet, and it was touted as a leader in L2.

Following the airdrop announcement and confirmation of the snapshot date, network activity on zkSync Era immediately collapsed. The 7-day average number of active addresses plummeted from a peak of 455,000 at the end of February 2024 to 218,000 in June, a drop of 52%. Daily transaction volume plunged from 1.75 million to 512,000. Notably, this crash occurred before the token distribution.

Nansen's data shows that among the first 10,000 wallets to receive the airdrop, nearly 40% of addresses sold all of their tokens within 24 hours. Only about 25% of the recipients chose to hold the tokens.

This dramatic drop in activity, which began even before distribution, confirms that the previous boom was entirely driven by external incentives. Once the studio deemed the "snapshot" complete, they immediately stopped the script execution. The data decline is merely a symptom; the real issue is the slap in the face to the project's narrative of "ecosystem prosperity."

3.3 LayerZero: Community Civil War and Trust Crisis Triggered by the Surrender Mechanism

The cross-chain interoperability protocol LayerZero is attempting a radical approach to combat witchcraft: introducing a "confession" mechanism. The project proposes a trade-off: if you confess to being a witch, you can retain 15% of the airdrop; if you conceal it and are discovered, you lose everything.

LayerZero ultimately identified and flagged over 800,000 addresses as potential Sybil attackers. This strategy sparked significant division within the community. Critics argued that it was unfair for LayerZero to directly label users of "volume-boosting tools" like Merkly as Sybil attackers, as LayerZero had previously benefited from the cross-chain fees and transaction volume data generated by these users.

Although this "purge" redistributed tokens to so-called "persistent users," $ZRO still faced a 23% price drop within a week of its listing. More seriously, the "Witch Bounty Hunter" scheme led to community members reporting each other, creating an extremely malicious atmosphere of surveillance and confrontation that severely damaged the project's brand reputation.

IV. The phenomenon of bad money driving out good money in the digital asset field

In economics, when exchange rates are fixed, bad money drives out good money. In the context of crypto user acquisition, this phenomenon manifests as fake users driving out real users.

4.1 Several Methods of Expulsion Mechanisms

Reward dilution: Airdrops are often a zero-sum game. Project teams allocate a fixed percentage (e.g., 10%) of their tokens to the community. If a studio controls 10,000 wallets, they take a huge slice of the prize pool, drastically diluting the share for real users who only have one wallet. When real users find that a year of normal use only yields negligible rewards, their willingness to participate in the ecosystem approaches zero.

Network congestion and soaring fees: Industrialized volume manipulation consumes valuable block space. During peak volume manipulation periods (such as Linea Voyage or Arbitrum Odyssey events), gas fees skyrocket. Real users, unable to afford the high transaction costs, are forced to migrate to other chains or cease using them. The network is ultimately left with only bots—because bots can amortize the high gas fees through the anticipated high airdrop rewards, while the utility gains of real users cannot cover this cost.

Complex Mechanisms: Some TGE projects, in an attempt to deter robots, intentionally designed incredibly complex interactive tasks, unaware that the complexity of the mechanisms is so great that even humans would be deterred; only tireless robots could complete them. Interestingly, some commentators have remarked that the 2025 Perp Dex battle has already evolved into a scripting war.

4.2 "Noise Surface" and Signal Loss

The proliferation of studios has raised the noise floor of the entire ecosystem. With 80%-90% of traffic being inorganic, project teams are simply unable to determine the true product-market fit.

In this environment of intense data pollution and toxic transactions, traditional A/B testing, user feedback loops, and feature adoption metrics become completely ineffective. Ultimately, the project team begins to optimize the UI/UX based on script preferences (e.g., reducing clicks to facilitate script execution, rather than prioritizing human usability).

The market has fallen into a "Market for Lemons" dilemma. High-quality projects that refuse to inflate their metrics and whose data appears "quiet" are undervalued by the market; while low-quality projects that actively cooperate with metrics inflation and whose data appears "booming" gain funding and attention. Ultimately, high-quality projects are forced to exit or join the ranks of those engaging in fraudulent practices, leading to a decline in the overall quality of the market.

4.3 The Project Owner's "Intoxication" and Conspiracy

Under the influence of the prevailing environment and the tacit approval of exchanges, some project teams have become "intoxicated" by superficial data. Impressive statistics are the only proof they can offer to investors and the public. Admitting that 90% of their users are fake will lead to a collapse in valuation and may not only prevent them from listing on exchanges but also result in lawsuits from investors.

Therefore, project teams fall into a kind of "performative ignorance." They might implement seemingly strict anti-cybernetics measures (such as banning some low-level scripts), but deliberately leave "backdoors" for high-end studios. The co-founder of Layer3 even publicly admitted that some projects do not want to implement strict bot filtering because they are optimizing scale metrics that drive narratives and funding.

This collusion completes a closed loop: project teams need fake data to sell to VCs/exchanges; studios provide fake data to sell to project teams; and VCs/exchanges sell the packaged projects to retail investors.

V. Conclusion

The current industry is like an athlete who has taken too much performance-enhancing drugs (fake data). Although the muscles (TVL, number of users) have expanded in the short term, the internal organs (real revenue, community consensus) have already failed.

What was originally a cyberpunk path to change the world has degenerated into a performative economy, where projects pay fees or sign options with studios to "produce" data that meets the standards arbitrarily set by exchanges and VCs.

It's not that the studios are doing anything wrong or bad; after all, it's a business activity, and where there's demand, there's supply. But when the entire market is filled with studios and signs of incentivizing traffic, things change.

This closed-loop profit model of "project team-VC-exchange-studio" is a typical negative-sum game. It maintains short-term paper prosperity by depleting the industry's credit reserves. To break this vicious cycle, the industry must undergo a painful deleveraging process.

For project teams, the pursuit of exchange listing qualifications replaced the exploration of product-market fit (PMF). Projects were designed to be "swiped" rather than "used." Furthermore, hundreds of billions of dollars in token incentives—originally intended to launch a genuine community—were siphoned off and arbitrage-driven by professional withdrawal bots, ultimately leading to abandonment.

This is not just a case of bad money driving out good, but also a case of falsehood driving out reality. Unless the industry can shift its focus from vanity metrics such as "active addresses" and "number of transactions" to attracting real-world use cases and creating genuine economic value, we will only go further down the path of bad money driving out good.

The studio won the airdrop battle, but their victory could cost the crypto industry the war on mass adoption.

Perhaps only when the benefits of "using the product" outweigh the benefits of "data manipulation" can good cryptocurrencies return, and the crypto industry truly escape the quagmire of a falsely prosperous financial game and move towards the other side of technology implementation.

In 2026, may we be clumsy players in this era where "data is king".