Hair Economics: The Hidden Symbiotic Chain between Project Providers, VC and Studio

Around the winter of 2020, the project\'s goal was alienated from \"creating value and serving users\" to \"providing services and serving the studio well.\" The core driving force behind this phenomenon lies in the contradiction between the exchange\'s rigid demand for data and the cold start of early projects. Due to the lack of real initial users and data, the exchange needs this data: the project party is forced to \"collude\" with the studio to create false prosperity through swiping and meet market expectations.

This model leads to project parties directly \"To Exchange\" and \"To Airdrop Hunter\". In this context, the industry has a phenomenon of \"bad money driving out good money\", that is, false interactive behaviors for the purpose of arbitrage (bad money) crowd out network resources and expel real ones by diluting rewards and pushing up use costs., Utility-oriented users (good money).

Originally used as an \"airdrop\" mechanism for marketing campaigns to attract new users, its original intention has completely failed and has become a blood transfusion mechanism for feeding studios and robots. Project parties and exchanges are addicted to this kind of data representation piled up by scripts, which not only leads to a huge waste of resources, but also fundamentally misleads the development direction of the industry.

This article aims to discuss the root causes, mechanisms and impact on the future of the industry. We will explore how first-tier exchanges represented by Binance and OKX have unintentionally become the \"baton\" of this distorted incentive mechanism through their listing standards; and analyze how venture capital institutions have adopted the \"high FDV, low circulation\" token economics design, and formed a secret symbiotic relationship with the \"Hair Slack Studio\" to jointly complete this big drama of false prosperity.

I. The incentive structure of the \"false\" economy: alienation from value creation to mere listing

The proliferation of hair-raising studios is not accidental chaos, but a rational economic response to the established incentive structure of the current cryptocurrency market. To understand why the project party even \"acquiesces\" to the existence of the studio, we must first analyze the survival rules set by the \"gatekeepers\"-CEX, VC, and KOL-who have the power of life and death in the industry.

1. Gatekeeper effect of exchanges: Data is admission ticket

In the current token economy model, for most infrastructure and middleware agreements, completing a \"grand slam\" listing on a first-tier exchange (such as Binance,OKX,Coinbase) is the definition of project success. This is not only a necessary liquidity event for early investors to withdraw, but also a sign that the project has gained mainstream market recognition. However, the exchange\'s listing standards have objectively created the demand for false data.

Exchanges \'review of listing applicants relies on quantitative indicators. As the exchange with the largest market share, Binance\'s listing standards openly emphasize \"strong community support\" and \"sustainable business model\", but in actual operation, transaction volume, daily active addresses, number of transactions on the chain, and TVL are often given higher weights. OKX also made it clear that in addition to technical aspects, they are extremely concerned about \"adoption rate indicators\" and \"market competitive position.\"

This mechanism creates a typical \"cold-start paradox\": a new Layer 2 or DeFi protocol requires real users to qualify for listing, but it is difficult to attract real users without the liquidity and token incentives expected from listing. Hairbrushing Studio has just filled this vacuum by providing a \"growth-as-a-service\" solution. Through automated scripts, the studio can create hundreds of thousands of daily active addresses and millions of transactions in a short period of time, drawing a perfect growth curve to meet the data requirements of the exchange\'s due diligence team.

This pressure is also reflected in the rumors of the so-called \"listing fee\". Although head exchanges such as Binance often deny charging high listing fees and emphasize the transparency of fees, in fact, project parties often need to commit a certain amount of trading volume liquidity or provide a large number of tokens as marketing budgets. If the project itself does not have enough natural flow, it must rely on market makers and studios to maintain this false prosperity to avoid being removed from exchanges or placed on watch lists.

2. VC\'s pressure cooker: vanity indicators and exit liquidity

VC plays a contributing role in this ecosystem. In the past cycle, billions of dollars have poured into infrastructure tracks. VC\'s business model determines that they must seek an exit path. The standard life cycle of a crypto project includes a seed round, a private placement round, and ultimately TGE and IPO.

During the TGE stage, the valuation of the project is highly correlated with market popularity and discussion level. 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 \"number of users.\"

The number of transactions is interpreted as \"demand for block space\",\"user activity\"

TVL is interpreted as \"trusted capital size\",\"cold start capital\"

Affected by the industry\'s purges and previous myths of sudden wealth, the crypto industry has attracted many short-attention speculators who prioritize these \"soil indicators\" over real value. VCs know they are competing with retail investors for limited liquidity, so they will pressure their portfolio companies to maximize these numbers ahead of TGE.

This creates a serious moral hazard: VC has the incentive to turn a blind eye to Sybil\'s activities, or even push behind the scenes, because it is the data contributed by these studios that supports their highly valued exits. So you will see that the Twitter accounts of some TGE projects have nearly one million followers, nearly one hundred million interactive addresses, billions of transactions, and so on.

While total registered users or raw transaction volume may seem convincing on the surface, they often lack correlation with the long-term success of the business. However, at the negotiating table in the primary market, these indicators are standard conditions and an entry threshold. A project with 500,000 \"active addresses\"(even if 99% are robots) is often valued much higher than a project with 500 true high-net-worth users.

3. Alienation of marketing activities: From acquiring customers to feeding robots

The original purpose of Airdrop was designed as a decentralized marketing tool aimed at distributing tokens to real users, thereby activating network effects. However, under the current incentive structure, the nature of airdrops has undergone a fundamental qualitative change.

Projects found that instead of spending budgets to educate the market and find real users (a slow and expensive process), they might as well attract studios by implying expectations of airdrops. This kind of \"point-based\" or \"task-based\" marketing activity is essentially a transaction to purchase data (some people say it is a long-term discount purchase of coins). The project party pays (or promises to pay) tokens, and the studio delivers data, gas fees and transaction fees on the chain. This kind of transaction is beneficial to both parties in the short term: the project side gets beautiful data that can be displayed to the exchange and VC, and the studio gets the expected token return.

But the victims of this collusion are the product culture and real users across the industry. Because the studio only needs to meet the minimum interaction threshold (for example, once a week for an amount greater than $10), the project\'s product iteration has also begun to be optimized around these robot and scripted interaction logic rather than optimizing the real user experience. This led to the birth of a large number of \"zombie protocols\" that were useless except for swipe volume-because the functions in them were all designed for robots. Come on, no one will come all the way from chain a to chain b for swap with a $10 token, okay?

Second, the industrialization operation mechanism of the hair-rolling studio (supply-side analysis)

The term \"hair-rolling studio\" has a certain grassroots color, and even contains some online jokingly jokes. It is a self-deprecating self-deprecation by the community, but in the context of 2024-2025, it refers to a high-tech industry that is highly professional, capitalized, and even has professional software development capabilities. These entities operate at the efficiency of software companies, using complex tools, sophisticated algorithms, and infrastructure to maximize the exploration of reward mechanisms.

1. Industrial-grade infrastructure and automation

The threshold for participating in Sybil attacks has been significantly lowered, mainly due to the popularity of professional tools. Fingerprint browser tools such as AdsPower and Multilogin allow operators to manage thousands of separate browser environments on a single computer. Each environment has a separate digital fingerprint (User Agent,Canvas Hash,WebGL Data, etc.) and a separate proxy IP address. This makes anti-cheating methods based on traditional Web2 technology (such as detecting logins on the same device) completely ineffective.

A typical studio operating process includes the following highly industrial aspects:

Identity masquerading and isolation: Use fingerprint browsers to isolate the local storage and cookies of thousands of wallets, ensuring they appear on the front end like unrelated, independent users from around the world.

Bulk wallet generation and management: Use hierarchical deterministic (HD) wallet technology to generate addresses in batches. In order to avoid on-chain clustering analysis, the studio will use CEX that supports sub-accounts for fund distribution. Since CEX\'s hot wallet address is universal, this cuts off the connection between the source of funds on the chain and breaks the fund tracking map commonly used by \"witch hunters\". (Advanced versions will also stagger the transfer time, transfer amount, etc.)

Scripted interactive execution: Write Python or JavaScript scripts, combined with automated testing frameworks such as Selenium or Puppeteer, and perform on-chain interactions around the clock. These scripts not only automatically complete operations such as Swap, Bridge, and Lending, but even introduce random modules to simulate human operation intervals and amount fluctuations to deceive behavior analysis algorithms.

KYC supply chain: For projects that attempt to block studios by mandatory KYC(such as CoinList public offerings or verification of certain projects), the underground market has formed a mature KYC data industry chain. Studios can purchase real identity information and biometric data in bulk from developing countries at extremely low cost, and even use AI technology to completely penetrate the defense line of Proof of Personhood through in-vivo testing.

2.\"Mission Platform\": Industrial Training Base and Colleagues

Another key development in this cycle is that in addition to Web3 mission platforms such as Galxe,Layer3,Zealy, and Kaito, regular military wallets and project parties, such as Binance alpha, various Perp Dex, and various emerging L1s, have also joined the ranks. These platforms ostensibly position themselves as a tool to educate users or build communities, rewarding users with points or NFTs by issuing \"tasks\"(such as \"Cross-chain ETH to Base\",\"Make a redemption on Uniswap\").

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

Layer3 is actually operating a \"growth-as-a-service\" market. The parties pay Layer3 in exchange for traffic, and Layer3 distributes these tasks to users. For studios, Layer3 clearly lists the interaction paths recognized by the project party. Studios only need to write scripts for these specific paths to obtain \"officially certified\" interaction records at the lowest cost.

Kaito is another service market for renting media buy. It is filled with the voices of a large number of AI robots, which indirectly encourages Twitter to be filled with various AI comments and invalid tweets.

Galxe allows project parties to create tasks that include on-chain interactions and social media attention. Although Galxe provides some anti-witch features (such as Galxe Passport), these features are often premium options for fees, and many project parties deliberately do not turn on strict filtering in order to maximize the number of participants.

What\'s even more ironic is that these platforms unintentionally (perhaps intentionally) train robots. By standardizing complex interactions into a linear \"Task A+ Task B= Reward,\" they create a deterministic logic that scripts are best at handling. The result is a large number of \"mercenary users\" who mechanically complete the minimum actions required to receive rewards and stop all activities as soon as the task is completed.

3. Economic ledger of hairdressing: ROI-driven capital allocation

The essence of hairdressing studio is capital allocation strategy. On the studio\'s ledger, Gas fees, slip point losses and capital occupation costs are considered customer acquisition costs. They calculate the input-output ratio (ROI).

If you spend a $100 Gas fee on a cluster of 50 wallets and you end up earning $5,000 worth of airdrop tokens, the ROI is as high as 4,900%. Such huge profits have been common in history:

Starknet case: An ordinary GitHub developer account can earn approximately 1,800 STRK tokens. At the beginning of the token\'s release, the price exceeded $2, which meant that revenue for a single account exceeded $3,600. If a studio uses scripts to register and maintain 100 GitHub accounts in batches, its total revenue will exceed $360,000.

Arbitrum case: Arbitrum\'s airdrop distributed approximately 12.75% of the total token amount. Even wallets with minimal interaction records can receive thousands of dollars worth of ARBs. This huge injection of liquidity not only verified the feasibility of the studio model, but also provided them with enough ammunition (capital) to launch larger-scale attacks in the next cycle (e.g. zkSync,LayerZero,Linea).

This high return creates a positive feedback loop: the successful airdrop provides funding for the studio to develop more complex scripts, purchase more expensive fingerprint browsers and proxy IPs, and thus occupy a larger share of the next project, further squeezing the living space of real users.

3. The ruins under the data appearance: currency issuance. People go. The building is empty.

The consequences of the studio\'s \"victory\" are nakedly demonstrated in the dismal performance of the main agreement after the airdrop. This reveals a clear pattern: Manufacturing growth-airdrop snapshots-retention collapse.

1. Starknet: Avalanche of Retention rate and extremely high cost of customer acquisition

Starknet, a high-profile ZK-Rollup network, implemented a large-scale STRK token airdrop in early 2024. Its distribution standards are quite broad and are designed to cover developers, early users and Ethereum pledgers.

This figure is amazing. On-chain analysis after the airdrop showed that among the users who received the airdrop, only about 1.1% of the addresses remained active thereafter. This means that 98.9% of the profitable addresses are mercenary in nature, and they stop contributing to the ecosystem immediately after taking away the reward.

Starknet actually spent approximately US$100 million (based on token value) to acquire approximately 500,000 users. However, considering a 1.1% Retention rate, its acquisition cost for a single retained user soared to more than $1,341. This is a catastrophic number that is completely economically unsustainable for any Web3 protocol or Web2 company.

This selling pressure caused the STRK token price to plummet 64% after launch. Although the total market value appears to have increased due to the token unlocking program, the purchasing power of the token itself has shrunk significantly.

Starknet\'s case provides a textbook-like negative lesson: users who expect to \"buy\" through airdrops are just phantoms. The studio extracts value and transfers it to the next battlefield, leaving the agreement with bloated historical data and empty block space.

2. zkSync Era: The end of the \"era\" and the cliff of data

ZkSync Era\'s trajectory is exactly the same as Starknet. Before the airdrop snapshot, the network\'s number of active addresses grew exponentially, often surpassing the Ethereum main network, and was touted as the leader of L2.

With the release of the airdrop announcement and confirmation of the snapshot date, network activity on zkSync Era immediately crashed. The average number of active addresses on the 7th dropped from a peak of 455,000 at the end of February 2024 to 218,000 in June, a drop of 52%. Daily trading volume plummeted from 1.75 million to 512,000. It is worth noting that this plunge occurred before the token distribution.

Nansen\'s data shows that of the first 10,000 wallets receiving airdrops, nearly 40% of addresses sold all their tokens within 24 hours. Only about 25% of recipients choose to hold tokens.

This slump in activity, which began before distribution, confirms that previous booms were driven entirely by external incentives. Once the \"snapshot\" is considered complete by the studio, they immediately stop the script running. The decline in data is only an appearance, but the face to the project party\'s \"ecological prosperity\" narrative is the truth.

3. LayerZero: Community civil war and crisis of trust caused by the surrender mechanism

Cross-chain interoperability protocol LayerZero attempts to adopt a radical approach to confront the studio: launching a \"surrender\" mechanism. The project party proposed a deal: if you admit that you are a witch, you can keep 15% of the airdrop share; if you conceal it and are discovered, you will have nothing.

LayerZero ultimately identified and flagged more than 800,000 addresses as potential witch attackers. This strategy caused a huge rift in the community. Critics point out that it is unfair for LayerZero to directly characterize users who use \"swipe tools\" such as Merkly as witches, because LayerZero has previously benefited from cross-chain fees and transaction volume data generated by these users.

Although this \"cleansing\" redistributed tokens to so-called \"persistent users,\"$ZRO still faced a 23% price drop within a week of its launch. More seriously, the \"Witch Bounty Hunter\" program caused community members to report to each other, creating an extremely vicious atmosphere of surveillance and confrontation, and seriously damaging the project\'s brand reputation.

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

In economics, when the exchange rate is fixed, bad money drives out good money. In the context of encrypted user acquisition, this phenomenon is reflected in: fake users expel real users.

1. Several ways of eviction mechanisms

Reward dilution: Airdrops are usually zero-sum games. The project party allocates a fixed proportion (such as 10%) of tokens to the community. If a studio controls 10,000 wallets, they cut a huge pie from the prize pool, greatly diluting the share of real users who only own one wallet. When real users find that their normal use for a year can only be exchanged for insignificant rewards, their willingness to participate in the ecosystem will approach zero.

Congestion and soaring costs: industrial swiping consumes valuable block space. Gas fees spike during peak brush times, such as during Linea Voyage or Arbitrum Odyssey campaigns. Real users are forced to migrate to other chains or stop using them because they cannot afford the high transaction costs. The network ends up with robots-because robots can amortize high Gas costs with high expected airdrop returns, which real users cannot cover with utility gains.

Complex mechanisms: In order to block robots, some TGE projects deliberately design interactive tasks to be extremely complex. However, the complexity of the mechanisms has already deterred natural people, and only tireless robots can complete them. Interestingly, some commentators claim that the 2025 Perp Dex War has evolved into a script war.

2.\"Noise floor\" and signal loss

The proliferation of studios has increased the Noise Floor of the entire ecosystem. When 80%-90% of the traffic is inorganic, the project party cannot judge the true Product-Market Fit.

In this kind of high-intensity data pollution and toxic transaction, traditional A/B testing, user feedback loops and functional adoption rate indicators completely fail. Eventually, projects began to optimize UI/UX based on script preferences (e.g., reducing clicks to facilitate script execution, rather than human ease of use).

The market is in a \"Market for Lemons\" dilemma. High-quality projects that refuse to brush the amount and whose data appears to be \"deserted\" are underestimated by the market; while low-quality projects that actively cooperate with the amount and whose data appears to be \"hot\" receive funding and attention. In the end, high-quality projects were forced to withdraw or collude with each other, resulting in a decline in the overall quality of the market.

3.\"Intoxication\" and collusion by the project parties

Under the influence of the general environment and the tacit consent of the exchange, some project parties began to \"intoxicated\" by the data appearance. Beautiful data is the only evidence that the project party can submit to investors and the public. Admitting that 90% of your users are fake will lead to a collapse in the valuation and may not only be unable to go to the firm, but also face litigation from investors.

As a result, the project party fell into a kind of \"performative ignorance.\" They will implement some seemingly strict anti-witch measures (such as blocking low-level scripts), but deliberately leave a \"back door\" for advanced studios. The co-founders of Layer3 even openly admit that some projects do not want strict robotic filtering because they are optimizing size metrics that drive narrative and financing.

This collusion completes the closed-loop-the project party needs fake data and sells it to the VC/exchange; the studio provides fake data and sells it to the project party; and the VC/exchange sells the packaged project to retail investors.

5. Conclusion

The current industry is like an athlete who has smoked too much stimulants (false data). Although his muscles (TVL, number of users) expand in the short term, his internal organs (real income, community consensus) have exhausted.

It turned out to be a cyberpunk road to change the world, but the encryption ecosystem has been transformed into a Performing Economy, where project parties pay fees or sign options to studios to \"produce\" data that meets the requirements of exchanges and VCs.

It\'s not that the studio is doing something wrong or bad. After all, it\'s all business activities. If there is demand, there is supply. However, when the entire market is filled with traces of studios and incentive traffic, things change.

This closed-loop interest of \"project party-VC-exchange-studio\" is a typical negative-sum game. It maintains short-term paper prosperity by draining the industry\'s credit reserves. To break this vicious cycle, the industry must go through a painful \"deleveraging\" process.

For project parties, the pursuit of exchange listing qualifications has replaced the exploration of product market fit (PMF). Projects are designed to be \"brushed\" rather than \"used\". In addition, tens of billions of dollars in token incentives-originally intended to start real communities-were siphoned, arbitrated, and ultimately abandoned by professional extraction machines.

This is not only bad money driving out good money, but also false driving out truth. Unless the industry can shift from focusing on vanity indicators such as \"active addresses\" and \"number of transactions\" to attracting real use scenarios and creating real economic value, we will only go further and further on the road of bad money driving out good money.

The studios won the battle for airdrops, but their victory may have cost the crypto industry the battle for mass adoption.

Perhaps, only when the benefits of \"using products\" are greater than the benefits of \"swiping data\" can good money return, and the encryption industry can truly emerge from the quagmire of false and prosperous financial games and move towards technology. The other side of implementation.

2026, May we be clumsy players in this era of \"data is king\"