Automated Market Makers (AMMs) have been one of DeFi’s most unique innovations, democratizing liquidity provision, enabling 24/7 trading without centralized intermediaries, and bootstrapping markets that would never form on a traditional exchange. They're often compared to Central Limit Order Books (CLOBs), the dominant model in traditional finance and on centralized crypto exchanges. Most of these comparisons focus on surface-level trade-offs: gas efficiency, latency, slippage, impermanent loss, and so on.
But there’s a deeper reason AMMs have become the default for trading in the realm of meme coins and other hard-to-value assets. Specifically, these assets don’t have cash flows, roadmaps, earnings, or fundamentals. There’s no quarterly report, no data room, no edge to be had from digging through filings. In short, there are no informed traders. Prices are driven by liquidity, flow, and noise; by memes, momentum, and vibes. In markets like these, volume is the only signal that matters.
That’s where AMMs shine. In a market with little to no informational edge, the risk of adverse selection disappears. The AMM doesn’t need to worry about being picked off by a hedge fund analyst or an insider. Instead, it becomes a neutral, transparent liquidity layer simple, scalable, and perfectly suited for noise-driven assets. If you built a CLOB for these tokens, it would likely behave like an AMM anyway.
CLOBs & AMMs
In traditional and centralized markets, the dominant mechanism for price discovery and execution is the Central Limit Order Book (CLOB). In a CLOB, traders submit limit orders to buy or sell at specific prices, forming a public queue of resting orders on both sides of the market. Trades occur when a market order hits a resting limit order, or when two overlapping limit orders cross. This structure allows for precise control over pricing and execution, and supports complex strategies like iceberg orders, time-priority algorithms, and layered liquidity.
Automated Market Makers (AMMs) are on-chain mechanisms that allow users to trade directly against token reserves held in a smart contract, rather than matching with counterparties through a traditional limit order book. This simple idea, swapping against a pool, hides a surprising amount of economic structure. At the heart of every AMM is a pricing function: a rule that defines how the exchange rate between two tokens changes based on the relative quantities in the pool. The most well-known of these is the constant product formula introduced by Uniswap v2, where the product of the token reserves must remain constant.
This mechanism enables continuous price discovery without relying on market participants to post limit orders. Instead, anyone can become a liquidity provider (LP) by depositing both tokens into the pool at the current price. In return, they receive LP tokens that represent their pro-rata share of the pool. As traders swap assets, they pay a small fee, which is added to the pool and distributed proportionally to LPs. Over time, LPs earn revenue from this swap activity, but this comes with a hidden risk.
That risk is called impermanent loss, which is a somewhat euphemistic name for what is, in many cases, permanent underperformance relative to simply holding the two assets outside the pool. When the price of one asset rises relative to the other, the AMM rebalances the pool to maintain its pricing function, which means LPs end up holding less of the appreciating asset and more of the depreciating one. The further the price moves away from the point where liquidity was initially provided, the worse this effect becomes. The loss is “impermanent” only in the narrow case where prices revert exactly to their original ratio. In practice, they usually don’t.
Despite this drawback, the simplicity of AMMs is exactly what makes them so powerful. An AMM is essentially a mechanical market maker: a predefined quoting strategy embedded into a smart contract. It doesn’t analyze order flow, it doesn’t respond to news, and it doesn’t update quotes dynamically like a human or algorithmic trader on a CLOB would. It simply says: “Given the current pool balances, here is the price you get.” There’s no need to model volatility, directional risk, or flow toxicity; just pure inventory-based pricing. Because of this, AMMs are best thought of as off-the-shelf market making algorithms, a plug-and-play replacement for a professional market maker, available to anyone with tokens to deposit.
From the outside, AMMs and Central Limit Order Books (CLOBs) may look structurally different, AMMs are smart contracts with continuous pricing curves, while CLOBs are collections of discrete limit orders placed by individual traders. But fundamentally, both mechanisms serve the same purpose: they define a supply curve for trading an asset (and also demand). In a CLOB, that supply curve is constructed from a stack of individual limit orders at various prices. In an AMM, it’s encoded in a mathematical formula that spreads liquidity continuously across price levels.
This connection is more than just theoretical. With enough resolution, you can reconstruct the implied virtual order book of an AMM by computing the marginal price at each infinitesimal unit of trade size, effectively sampling the slope of the pricing curve. And when aggregating across multiple pools via a DEX router, the result is an on-chain composite order book, even though none of the liquidity providers explicitly posted any limit orders. The supply curve still exists, it’s just implicit in the reserves and formulas, not explicitly typed in by hand.
Why Different Market Structures Exist
Not all markets are created equal, and neither are the assets traded within them. The structure of a market isn’t just a technical detail; it reflects the nature of the product itself: how it trades, how it’s valued, and how participants interact. Different market architectures, whether Central Limit Order Books (CLOBs) or Automated Market Makers (AMMs), are optimized for different kinds of assets. And understanding which structure fits where can explain why certain financial products thrive in one environment but fail in another.
Start with the CLOB, the gold standard for highly liquid, high-information assets like equities, futures, or large-cap crypto. In these markets, pricing is a continuous, information-driven process. New data, earnings reports, macro news, order flow, and geopolitical developments, constantly reshapes participants’ view of fundamental value. That informational edge drives active quoting, tight spreads, and competitive liquidity provision.
A CLOB allows traders to position themselves precisely in response to evolving information and compete on price and time priority. This works because there's enough informational depth to justify differentiated quoting, and enough liquidity to ensure orders are filled without excessive slippage. Informed traders need a venue where they can express directional views efficiently, and passive liquidity providers can earn the spread if they manage inventory and adverse selection risk. In this context, AMMs would get picked off instantly, they’re too passive, too symmetric, and too blind to flow.
But now contrast this with AMMs, which shine in markets where liquidity is fragmented or difficult to bootstrap, and where the informational value of order flow is minimal or non-existent. This describes a huge swath of on-chain markets, especially memecoins and even tokens of nascent projects. These assets often have no periodic earnings, no actual fundamentals, and no real way for any trader to possess meaningful informational edge. Their price is driven by narrative, social momentum, and raw demand, not research. As such, the imbalance of volume itself capture most of the information there is about the value of the asset.
AMMs can therefore offer continuous, passive liquidity that doesn’t rely on active participation. The pricing curve encodes a mechanical response to flow, and anyone can provide liquidity by plugging into the curve. It’s not perfect, but in a world with no real information, you don’t need perfect. You need accessible and permissionless, and that will get you much further than a CLOB which needs the support of professional market-maker algorithms.
Should Market Making Be Democratized
AMMs, at their core, raised a fundamental question: should market making be democratized? In other words, should anyone be able to provide liquidity, earn fees, and participate in price discovery, without any edge, infrastructure, or experience?The answer we give is: yes, initially, but less so, eventually. And that arc tells you something about where AMMs and CLOBs each belong in the lifecycle of an asset.
In the early stages of a market, liquidity is a bottleneck. New tokens face a classic chicken-and-egg problem: no one wants to trade an illiquid asset, and without trades, the asset stays illiquid. This dynamic imposes a liquidity discount on early projects, one that raises their cost of capital and often gives an unfair advantage to large, well-funded tokens that can afford to negotiate CEX listings or pay market makers.
Democratized liquidity, via AMMs, solves this elegantly. Anyone can spin up a pool, deposit two tokens, and immediately create a market. There’s no need to convince a professional market maker to care, and no need to rely on centralized gatekeepers. AMMs effectively hand every user a deterministic, off-the-shelf market making algorithm, making it possible for even the smallest project to bootstrap trading.
This is where the yes part of the answer lives: democratized market making is the right tool for bootstrapping liquidity, especially for assets that traditional market makers would never touch. The AMM acts as a neutral liquidity layer, powered by community members or early investors, and allows price discovery to begin long before there's enough volume to attract professionals. This lowers the barrier to entry for new assets, promotes experimentation, and decentralizes access to markets.
But over time, as an asset gains traction, informational efficiency begins to matter more. In this regime, market making becomes a low-margin, high-skill game, a business of speed, inventory management, and flow analysis. Deterministic curves like those used in AMMs simply can’t compete with human or algorithmic market makers who can respond to real-time conditions. And they don’t need to, because division of labor and specialization is a feature, not a bug. There’s nothing wrong with having professionals make markets on high-volume assets. That’s exactly what specialization is for: efficient capital allocation.
It’s also worth noting that professional market makers won’t touch every market. They’re highly selective because of the thin margins and infrastructure overhead. They need size, volume, and predictable behavior. For anything that doesn’t hit that bar, low-cap tokens, experimental protocols, small DAOs, AMMs are not just helpful; they’re essential. They keep the door open for markets that would otherwise have no liquidity at all.
So the correct framing isn’t “AMMs vs. market makers,” but rather: AMMs as the democratized entry point, and CLOBs + specialists as the high-efficiency endpoint. It’s a lifecycle. An asset should graduate from AMM liquidity to CLOB liquidity as it becomes more liquid, more information-sensitive, and more actively traded. The two systems aren’t in conflict, they’re complementary layers of a healthy market stack. In that sense, the enduring advantage of AMMs isn’t that they’ll replace professional market makers, it’s that they allow everything else to exist. Without AMMs, many assets would never get past the cold start.
Moreover, as AMM technology evolves, it is likely that AMMs can be profitable for LPs in expectancy even as assets become more informationally efficient; and while CLOBs may be central to price discovery, especially in mature markets like perpetuals on large-cap crypto, this does not mean that AMMs are incapable of generating profits for LPs. The profit of an AMM is largely determined by the supply and demand of liquidity. If demand outstrips supply, AMM LPs can still thrive.
Consider that even in traditional finance, where professional market makers dominate liquidity provision and price discovery, a small firm or even an individual with an exceptional market-making algorithm can still profit and generate positive PnL, even in the presence of highly liquid CLOBs. In this sense, even in mature markets, AMMs can serve as a complementary liquidity layer that allows decentralized liquidity provision to function alongside more capital efficient CLOBs.
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