Leaving behind the chaotic early days, crypto market makers are celebrating their coming of age
Source: TechFlow (Shenchao)
In the cryptocurrency sphere, market makers seem perpetually at the top of the food chain. They are seen as "systemic winners," alongside exchanges, imagined as "pumps" that reap profits from every market fluctuation without bearing directional risk.
However, a closer look into the industry reveals a harsher reality: some are wiped out overnight in extreme market conditions, others are forced to exit the market due to a single risk management lapse, and many more are forced to restructure their entire business model amidst halved profits, ineffective price wars, and a scarcity of quality assets.
The life of a crypto market maker is far from glamorous.
Over the past two years, the industry has undergone a quiet yet brutal purge. With the decline of exorbitant profits and tightening regulations, compliance capabilities, risk control systems, and technological expertise have replaced the former boldness and gray-area operations as the new survival threshold. This is no longer a game of "whoever is boldest makes money," but rather a long-term, professional, and low-tolerance survival competition.
In in-depth interviews with several leading market makers, a highly consistent assessment emerged: today's crypto market makers are no longer simply "liquidity providers," but are evolving into a hybrid model of "secondary market investor + risk manager + infrastructure."
As the tide recedes, competition returns to rationality, and risks are fully exposed, who is leaving the game? Who will remain?
From "Wild Arbitrage" to "Highly Institutionalized"
If we turn back the clock to 2017, modern "crypto market makers" were practically nonexistent.
Market making at that time was more like a frenzy of gray arbitrage. Borrowing, dumping, replenishing, returning... dumping tokens when liquidity was plentiful, and slowly accumulating tokens in the long tail. The boundaries between exchanges, project teams, and market makers were extremely blurred; price manipulation and fraudulent transactions, considered serious crimes in traditional finance, were commonplace at the time.
But time is relentlessly eliminating this model.
The consensus among many interviewees is that market makers in 2017 relied on boldness and information asymmetry; today, they rely on systems, risk control, and compliance.
The core of this change is not simply an "upgrade in gameplay," but a fundamental shift in the industry's underlying structure. In the past, whether market makers "followed the rules" might have been a moral choice; now, it's a matter of life and death.
Joesph, an investment partner at Klein Labs, revealed that all of their current operations must revolve around "auditability." Contractual compliance, financial audits, transaction details, and delivery reports have gone from "optional" to "default configuration." As a result, compliance costs now account for 30% to 50% of total operating expenses.
With the accelerated compliance process of exchanges, increased transparency in project financing paths, and the mainstreaming of regulatory narratives, the survival logic of market makers is being forced to restructure. The old, unregulated model of "black box operations + results-oriented" practices is being systematically eliminated.
A clear signal is that more and more market makers are incorporating "Regulation First" into their brand narrative, no longer avoiding the topic.
The shift in roles is equally profound. In the early days of the industry, market makers were merely the execution layer; project teams provided funds and tokens, and market makers were responsible for placing orders. Now, market makers are more like secondary partners.
"Whether we take on a project has become akin to an investment decision. The project's fundamentals, circulation structure, exchange allocation, and volatility range are all quantitatively assessed in advance," says Joesph. "Projects whose market capitalization doesn't even crack the top 1000 might not even qualify for discussion."
The reason is simple. A single poor-quality project can devour a market maker's entire year's risk budget. In this sense, market making is no longer a simple "service fee business," but a long-term game surrounding risk exposure.
Of course, arbitrage has not completely disappeared, but it has been marginalized.
In the industry's darker corners, high-risk, high-ambiguity operations still exist, but their scaling is increasingly difficult, and their survival space is extremely compressed. When exchanges, project teams, and market sentiment unanimously favor "steady liquidity," those who break the rules become a systemic risk.
In the current crypto market-making landscape, "following the rules" has, for the first time, transformed from a moral constraint into a core competitive advantage.
Excessive profits are disappearing.
Compared to the last bull market, project teams have significantly reduced their budgets for market makers. "Data shows that some projects have even reduced their token budgets by 50% this year compared to the previous round," noted Vicent, CIO of Kronos Labs.
But this is not merely a matter of "budget cuts"; the deeper driving force comes from the evolution of the mindset of the clients (project teams).
Project teams have significantly improved their understanding of market-making. They are beginning to understand the profit margins of market makers and are no longer satisfied with vague liquidity promises. Instead, they demand quantifiable KPIs, clear delivery logic, and in-depth explanations of the efficiency of each fund's use.
In short, less capital, higher demands.
Faced with this pressure, leading market makers have not blindly engaged in price wars. Vicent emphasizes that market making is an industry heavily reliant on systems, risk control, and experience. Once a price quote falls below the cost of risk coverage, market makers face not just declining profits, but a survival crisis. Therefore, when the risk-reward ratio is unbalanced, they prefer to abandon the business.
This means the market hasn't been completely overwhelmed by "low-price players," but rather a group of survivors who adhere to ethical standards has emerged.
Currently, another phenomenon is the scarcity of high-quality clients and the unprofitability of long-tail projects.
Reele of ATH-Labs stated, "The number of projects with genuine market-making value is far less than the number of market makers in the market." Many long-tail projects, due to insufficient depth or arbitrage opportunities, struggle to generate sustainable returns even if they meet market-making targets.
This leads to a classic "too many cooks spoil the broth" situation: top market makers are concentrated in high-quality projects, while smaller teams are forced into fierce competition on low-profit, high-risk, marginal projects.
In this context, market making is degenerating from a simple "profit center" into a "relationship entry point." Many market makers view market making as a stepping stone to long-term partnerships, using it as a starting point to enter project treasury management, OTC trading, structured products, and even become secondary market advisors or asset managers.
In other words, the real profits are increasingly not in the "market making fee," but in the subsequent structure. This explains why many still-active market makers are simultaneously expanding into investment, asset management, and advisory services; they are not transforming, but rather seeking "survival space" for a shrinking core business.
Industry Reshaping: The Splitting of the Table
In the previous cycle, competition among market makers mainly occurred at the same table: the same exchanges, the same product forms, and the same liquidity metrics.
This year, however, this table is being split.
The emergence of new tracks such as on-chain market making, derivatives, and stock tokenization is systematically changing the competitive landscape of market makers.
On a narrative level, on-chain market making is often labeled as "open and decentralized," but in practice, the barriers to entry are rising rather than falling. The uncertainty of real liquidity, the limitations of the execution environment, and the inherent risks of smart contracts make it a completely different capability curve, rather than a game-changer.
Compared to on-chain market making, derivatives market making exhibits the opposite characteristics. Its entry barrier is high, but once established, its competitive advantage is extremely deep.
In derivatives market making, the contract market demands extremely stringent risk control and position management, naturally favoring institutional market makers with larger capital, more experience in risk control, and more mature systems. New players are not without opportunities in this field, but the margin for error is extremely low.
As for stock tokenization, although it is considered a key narrative connecting traditional finance, it is still in its early stages in terms of market making. Its core difficulty lies in the complexity of hedging and settlement structures, leading most market makers to maintain a "research first, cautious participation" attitude.
In other words, this is a field with extremely high potential, but one where a stable market-making model has not yet been formed.
In Reele's view, these new market-making fields are not only reshaping the industry structure but also a source of pressure for their innovation. Although customer numbers have decreased, it's still crucial to adapt to the ever-evolving new market dynamics and provide projects with better market-making strategies.
"The market-making industry is transitioning from a 'unified market' to a structured ecosystem of 'multi-track parallel development.' Competition among market makers is shifting from 'homogeneous involution' to cross-track capability differentiation," Reele stated.
The Moat of Crypto Market Makers
As the era of exorbitant profits recedes, roles shift, and the market segment diversifies, a reality becomes clear: competition among market makers is no longer about who is more aggressive, but about who is less prone to making mistakes.
At this stage, what truly differentiates them is not a single advantage, but a comprehensive set of systemic capabilities that are difficult to replicate.
These systemic capabilities include a stable trading system, a rigorous risk control system, strong research capabilities, compliance, and auditability—all of which collectively build the trust system for crypto market makers.
Joesph reveals that the credit and compliance costs incurred in building this trust system are currently the biggest expenses. While the crypto market maker industry is already highly competitive, newcomers may not necessarily be more experienced than established market makers in building consensus, reputation, and managing risk.
The crypto market shake-up of October 11, 2025, serves as a case in point. Vicent stated that this incident reflects the fact that the transmission speed of leverage and liquidation is now far faster than traditional risk control response mechanisms; the industry is undergoing rapid differentiation, with teams lacking sufficient infrastructure and risk control capabilities being eliminated, and the market evolving towards a more concentrated and institutionalized direction.
“Market making is now a systematic project. Those teams that truly survive in the long run are not those that avoid a single risk, but those that assume from the beginning that a cleansing will inevitably occur and prepare for it,” Vicent said.
In summary, the true moat for market makers lies in their “lack of reliance on fatal mistakes” at multiple key junctures. This leads to a seemingly counterintuitive result: the most successful market makers are those that are most restrained, institutionalized, and systematic.
As the market enters a new phase of full competition and institutionalized risk management, crypto market makers are no longer “marginal arbitrageurs,” but rather an indispensable yet highly constrained foundational role in the crypto financial system.
Its survival logic is becoming increasingly similar to traditional finance, operating with the precision of Wall Street's high-frequency trading giants, yet it operates in a "dark forest"—a market that never closes 24/7 and has volatility ten times that of Nasdaq.
This is not merely a return to traditional finance, but a species evolution under extreme conditions.
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Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link

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