High-end stumbling blocks often appear disguised as stepping stones. Some call it a gift of the times, yet few realize that the cost has long been etched behind the noise—in the empty mirage that remains afterward.

How did the scenes of the crypto industry in 2025 become a mirage jointly created by project teams, venture capital, and airdrop farmers?

Around the winter of 2020, the objective of many crypto projects gradually shifted from “creating value and serving users” to “getting listed on exchanges and serving farming studios.”

The core driver behind this phenomenon lies in the contradiction between exchanges’ rigid demand for data and the cold-start problem faced by early-stage projects.

Because new projects lack real users and organic data at the beginning—while exchanges require precisely those metrics—project teams are effectively forced to collude with farming studios, manufacturing artificial prosperity through fake volume to satisfy market expectations.

This model has led to projects essentially “building for exchanges” (To Exchange) and “building for airdrop hunters” (To Airdrop Hunter).

Under this environment, the industry has begun to display the classic phenomenon of “bad money driving out good.”

Fraudulent interactions aimed purely at arbitrage (bad money) consume network resources and dilute rewards, while pushing out genuine users who interact with the network for real utility (good money).

Originally designed as a marketing mechanism to attract new users, airdrops have now completely lost their original purpose. Instead, they have become a blood-transfusion system feeding farming studios and bots.

Project teams and exchanges have become intoxicated by the illusion created by these script-generated data points. This not only wastes enormous resources, but fundamentally misguides the development direction of the entire industry.

This article explores the root causes, mechanisms, and long-term implications of this phenomenon.

We will examine how major exchanges such as Binance and OKX, through their listing criteria, unintentionally became the baton directing this distorted incentive system.

We will also analyze how venture capital firms—through tokenomics designs featuring high FDV (Fully Diluted Valuation) and low circulating supply—form a hidden symbiotic relationship with airdrop farming studios, jointly staging a grand performance of artificial prosperity.

1. The Incentive Structure of the “Fake Economy”

From Value Creation to Listing-Only Projects

The proliferation of farming studios is not random chaos—it is a rational economic response to the incentive structure of today’s crypto market.

To understand why projects even tolerate or tacitly accept these studios, we must first analyze the gatekeepers of the industry: centralized exchanges (CEXs), venture capital (VCs), and key opinion leaders (KOLs).

1.1 The Exchange Gatekeeper Effect: Data as the Ticket to Entry

In today’s token economy, for most infrastructure and middleware protocols, achieving a “grand slam listing” on major exchanges (such as Binance, OKX, and Coinbase) is considered the definition of project success.

This is not only the liquidity event needed for early investors to exit, but also a signal of mainstream market validation.

However, the listing standards of exchanges objectively create demand for fake data.

Exchange due diligence heavily relies on quantitative metrics.

For example:

  • Binance, despite publicly emphasizing community support and sustainable business models, still heavily considers metrics such as:

    • trading volume

    • daily active addresses

    • on-chain transactions

    • total value locked (TVL)

  • OKX similarly focuses on:

    • adoption metrics

    • market positioning

This leads to a classic cold-start paradox.

A new Layer 2 or DeFi protocol needs real users to qualify for listing.
But without the liquidity and token incentives that come from listing, it is extremely difficult to attract real users.

Farming studios conveniently fill this vacuum.

They offer “Growth-as-a-Service.”

Using automated scripts, studios can generate:

  • hundreds of thousands of daily active addresses

  • millions of transactions

in a short period of time, creating a perfect growth curve that satisfies exchange due diligence teams.

1.2 VC Pressure: Vanity Metrics and Exit Liquidity

Venture capital firms play a major role in amplifying this system.

Over the last cycle, tens of billions of dollars flowed into crypto infrastructure.

VC business models require exit liquidity, and the typical lifecycle of a crypto project is:

Seed → Private rounds → TGE → Exchange listing.

At the TGE stage, valuations depend heavily on market hype and metrics, since traditional valuation models like P/E ratios or discounted cash flows are largely absent in crypto.

Instead, proxy metrics are used:

  • Active addresses → interpreted as user numbers

  • Transaction count → interpreted as user activity

  • TVL → interpreted as trusted capital

Because the crypto market attracts many short-attention speculative participants, these superficial metrics often matter more than actual product value.

VCs know they are competing with retail investors for liquidity, so they pressure portfolio companies to maximize these metrics before TGE.

This creates serious moral hazard.

VCs have incentives to ignore or even encourage Sybil activity, since the data generated by farming studios supports higher valuations at exit.

Thus we see projects with:

  • nearly 1 million Twitter followers

  • hundreds of millions of interaction addresses

  • billions of transactions

—numbers that are often largely artificial.

1.3 The Mutation of Marketing: From User Acquisition to Bot Feeding

Airdrops were originally designed as a decentralized marketing mechanism to distribute tokens to real users and bootstrap network effects.

However, under the current incentive system, the nature of airdrops has fundamentally changed.

Instead of investing in real user education (which is slow and expensive), projects now hint at future airdrops to attract farming studios.

These point systems or task systems are essentially transactions for buying data.

Projects promise tokens.
Studios deliver:

  • on-chain interactions

  • gas fees

  • transaction activity

In the short term, both sides benefit.

Projects obtain impressive metrics to present to exchanges and VCs.
Studios receive expected token rewards.

But the real victims are:

  • product culture

  • genuine users

Because studios only meet minimum interaction thresholds (for example, one weekly transaction above $10), products are increasingly designed for bots rather than humans.

The result is the creation of “zombie protocols” whose only purpose is generating fake activity.

After all, no real user would bridge assets across chains just to swap $10 worth of tokens.

2. The Industrial Operation of Farming Studios

The term “airdrop farming studio” might sound grassroots or humorous, but in the 2024-2025 context it refers to a highly professionalized, capitalized, and technologically sophisticated industry.

These entities operate with the efficiency of software companies.

2.1 Industrial Infrastructure and Automation

The barrier to conducting Sybil attacks has dropped significantly thanks to professional tools such as:

  • AdsPower

  • Multilogin

These fingerprint browsers allow operators to manage thousands of isolated browser environments on a single computer, each with unique fingerprints and proxy IP addresses.

A typical farming studio workflow includes:

Identity masking
Thousands of wallets operate in isolated environments that appear as unrelated users globally.

Mass wallet generation
Using hierarchical deterministic wallets and CEX sub-accounts to break on-chain traceability.

Scripted interactions
Automated scripts perform swaps, bridges, and lending activities continuously, with random delays and values to mimic human behavior.

KYC supply chains
Underground markets sell real identity documents and biometric data, sometimes enhanced with AI to bypass liveness detection.

2.2 Task Platforms: Training Grounds for Bots

Task platforms such as:

  • Galxe

  • Layer3

  • Zealy

  • Kaito

were designed to educate users and grow communities.

But they have unintentionally become training camps for bots.

Layer3 essentially operates a Growth-as-a-Service marketplace, where protocols pay for traffic and tasks are distributed to users.

For studios, these tasks provide clear interaction blueprints.

Scripts can simply follow them.

Meanwhile platforms like Kaito amplify media noise through AI-generated content, flooding social media with low-quality posts.

Ironically, by simplifying complex interactions into linear tasks, these platforms have made it easier for scripts to automate everything.

The result is a large population of mercenary users who complete tasks purely for rewards and disappear afterward.

2.3 The Economics of Farming

At its core, farming is simply capital allocation.

Studios calculate ROI.

Gas fees, slippage, and capital costs are treated as customer acquisition costs.

For example:

Spend $100 on gas across 50 wallets → receive $5,000 in airdrops → 4,900% ROI.

Historical examples include:

Starknet

A single GitHub developer account could receive ~1,800 STRK tokens.
At $2 per token, that’s $3,600 per account.

With 100 accounts → $360,000 profit.

Arbitrum

Even minimal activity wallets received thousands of dollars in ARB tokens.

These successes created a positive feedback loop.

Profits from one airdrop fund better infrastructure for the next one.

3. The Ruins Behind the Data

The victory of farming studios is visible in the post-airdrop collapse of many protocols.

3.1 Starknet

After the STRK airdrop, only 1.1% of addresses remained active.

This means 98.9% were mercenary users.

Starknet effectively spent $100 million to acquire 500k users, but with retention considered, the cost per retained user exceeded $1,300.

3.2 zkSync Era

Before its airdrop snapshot, zkSync saw explosive growth.

But once the snapshot was taken:

  • active addresses dropped 52%

  • transactions collapsed dramatically

This confirmed the previous growth was purely incentive-driven.

3.3 LayerZero

LayerZero attempted a radical strategy:

Users could self-report as Sybils, keep 15% of rewards, or risk receiving nothing if caught.

Over 800,000 addresses were flagged.

But the policy triggered community infighting, damaging trust and brand reputation.

4. Bad Money Driving Out Good

In crypto user acquisition, the principle manifests as:

Fake users driving out real users.

Mechanisms include:

  • reward dilution

  • network congestion

  • rising gas fees

  • overly complex participation mechanisms

Eventually the ecosystem becomes dominated by bots, since bots can amortize costs with expected rewards while real users cannot.

5. Conclusion

Today’s industry resembles an athlete overdosed on stimulants.

Short-term metrics—TVL, user numbers—are inflated, while the internal organs of the ecosystem—real revenue and genuine communities—are weakening.

Crypto was supposed to be a cyberpunk revolution.

Instead, it risks becoming a performative economy, where projects pay studios to manufacture data that satisfies exchanges and VCs.

The issue is not that studios are doing something wrong—they are simply responding to market demand.

But when the entire market becomes dominated by this behavior, the system becomes a negative-sum game.

Studios may have won the airdrop battles, but their victory could cause the crypto industry to lose the war for mass adoption.

Only when using products becomes more profitable than faking usage will real users return.

And perhaps in this “data-is-king” era, the best thing we can do is remain clumsy players who still believe in building real products.

Source: https://x.com/agintender