# Crypto Is Rigged Against Founders (https://www.baseline.markets/blog/crypto-is-rigged-against-founders)
Date: 2026-03-11
Author: Unbanksy
85% of tokens launched in 2025 ended negative. Today's token launches introduce hidden costs that make it nearly impossible to recover from. People will tell you this is how crypto always was and always will be. It doesn't have to be.
To get a token live and tradeable, projects must choose between centralized exchanges, professional market makers, or onchain liquidity. Each one comes with its own hidden costs that all produce the same result: sell pressure at launch.
Arrakis reviewed 125 token launches and confirmed this. 85% of tokens launched in 2025 ended negative, and only 9% of tokens that dropped in week one ever recovered. The damage happens before the token even hits the trading chart.
## Centralized exchanges: the cost of distribution
Getting listed on a major exchange costs tokens. Projects report giving up 10% of total supply for a Tier 1 listing, plus months of due diligence that burns runway while you wait. Binance alone has teams stalled for months before they see a listing.
Founders convince themselves the distribution is worth the cost until they realize the exchange listing is the event that triggers the sell pressure: airdrop recipients dump and the listing you paid for in tokens becomes the venue of price destruction.
## Market makers: the cost of manipulation
Once listed, tokens need liquidity. Market makers offer a standard deal: loan us your tokens at a set price, and we provide liquidity. If we don't deliver, we return the tokens at a higher price after a year. Sounds reasonable but in reality: the MM may dump your loaned tokens, break service-level agreements, and trade against you at the cost of your chart and your community's trust.
For instance, CoinDesk investigated [@movement\_xyz](https://x.com/movement_xyz) MOVE token and found that [@Web3Port\_Labs](https://x.com/Web3Port_Labs) dumped 66M tokens one day after the Binance listing. Movement's own general counsel had called the deal "possibly the worst agreement I have ever seen". Binance banned the market maker, Coinbase delisted the token and the co-founder was suspended.
The deal is designed for the MM to win and for projects to lose. Some founders know what they're signing. Others get misled. Either way, the cost is the same.
## Onchain liquidity: the cost of renting
Some projects skip the middlemen and go onchain:
* Deploy a passive Uniswap V2 pool and hope for the best
* Try to manage concentrated V3 positions manually
* Bribe LPs through emissions programs paying with your own tokens
Going onchain removes the counterparty, but not the cost. Founders still need to understand how tokenomics impact their liquidity, manage pool positions as supply changes, and spend their own token supply to attract third-party LPs who leave when incentives dry up.
For instance, when \$SYND launched on [@AerodromeFi](https://x.com/AerodromeFi), the project allocated 1% of supply to bribe voters. The data shows that the majority of those wallets sold them immediately upon launch, translating to 1,729 ETH (\~\$7.78M) in sell pressure in the first week alone. Even worse, the liquidity churned when incentives ended, making the entire program a temporary benefit with a permanent cost.
Every path leads to the same place: the token gets dumped, insiders get paid, and buyers get rekt.
## Token Owned Liquidity
Baseline built an AMM where tokens own their liquidity. The design inverts every cost described above:
* **No unnecessary sell pressure:** the token's own supply bootstraps the liquidity, no bribes or loans to third parties who dump it
* **Permanent liquidity:** value stays in the pool and compounds from trading activity, instead of leaving when incentives rotate
* **Asset, not a liability:** trading fees and reserves accrue back to the token's balance sheet, not to external counterparties
To demonstrate what's possible, we simulated an existing onchain liquidity strategy against a Baseline pool. The results were impressive:
* **Price:** +59.6% higher from identical trade flow
* **Liquidity growth:** +267.7% more liquidity to sell into
* **Supply control:** +200.5% more tokens pulled out of circulation
* **Fees:** +81.1% more collected in trading fees without impacting tradeability
If you're interested in learning more about Baseline, check out our [docs](https://www.baseline.markets/docs).
If you're launching a token or running one that's costing you, we can simulate your trade data and show you the difference. DM [@basedbooo](https://x.com/basedbooo) or join our [Discord](https://discord.gg/baseline).
---
# Defeating the Death Spiral (https://www.baseline.markets/blog/defeating-the-death-spiral)
Date: 2025-10-22
Author: indigo
Death spirals. Bank runs. Negative reflexivity.
Similar concepts, different contexts. When confidence erodes and everyone rushes for the exit, escaping with whatever value they can get.
It represents the looming fate of tokens issued onchain. A gravitational pull to 0. More often than not, a token's destiny is already set the second it's deployed.
From 2020 to the present, onchain tokens have suffered from the same problems. Poor tokenomics combined with snipers and short-term extractors. A team member, investors or snipers dumping, wiping out all the positive momentum and leaving the rest to hold the bag. It's never been easy here.
It's one of the greatest fears for builders. Endlessly working and sweating for months to years, tokenomics becomes an afterthought. But the looming threat is always there: A token's price is its narrative. It will dictate the life and death of the project. A misstep in token allocations or misconfigured liquidity, and zero is inevitable.
The problem stems from the dynamics of the AMMs we have become accustomed to. Beautiful and elegant, but fundamentally flawed. A key problem is the simplistic pricing system of these pools, requiring constant maintenance to respond to market dynamics.
However, the more insidious issue lies not in the code, but in the nature of its liquidity. To understand the death spiral, we must look at the people who provide it.
## Liquidity For Hire
Although the AMM is autonomous, the liquidity provider (LP) for these AMMs is, more often than not, a human, and LPing is risky business. And thus, as a rational profit-seeking entity, whether an incentivized LP or a private market maker, the one providing the service of LPing must be compensated for taking that risk.
There's a reason these LPs are often called "mercenary liquidity". As soon as the flow of incentives stops, or it's unprofitable to hold the token, there's no reason for the LP to stay.
They're not evil. They're not trying to fuck anyone over. They're just human.
Liquidity is the lifeblood of markets. Without it, a market's structure is fragile and prone to collapse. What's needed to solve these problems is a different type of liquidity provider.
## History doesn't repeat, but it does rhyme
Stepping back, its good practice to look to TradFi for its many generations of learnings. Banking in the 19th and 20th centuries was going through similar problems of illiquidity. There were numerous examples of financial institutions collapsing, bank runs being a frequent occurrence.
Back then, the realization was that banks go through regular periods of illiquidity. If they could get an injection of capital when they needed it the most, they could survive the temporary downturn and bounce back.
The solution was the concept of a Central Bank. An entity with the objective of ensuring liquidity in the many banks it oversees. One that all banks can trust to protect them, with the purpose of providing the support it needs to thrive during good times, and survive during the bad.
The most interesting part of this solution though, is that the mere presence of such a backstop is often enough to prevent this negative reflexivity from starting in the first place.
A very powerful concept. What if we could do better?
What if it was possible to create a smart contract to serve the same purpose as a Central Bank, to provide that same kind of confidence for a token?
This would be a tool to fight the death spiral. An anti-reflexive engine.
## A New Type Of LP
This is Baseline's ultimate directive: to support a token through shifting market conditions, at every phase of its lifecycle. Like a financial battery, it gathers value during good times, and releases it back during the bad.
As an autonomous liquidity provider, Baseline efficiently supplies its Protocol-Owned Liquidity across top-of-book bids and asks, while preserving an ever-growing floor price to be the ultimate backstop for holders, providing support where and when it's needed most.
**A Central Bank for your token.**
From this core mechanism, we created a pricing system superior to the standard CPMM and a lending system free from brutal liquidations. We distribute the value these generate, establishing a native yield source for each token. These primitives combine to enable resilient onchain economies that can survive and thrive.
## Conclusion
We're a team of builders who have felt the pain of onchain trading for too long. We've been working on solving these issues for years. And we believe the problem isn't the builders or traders, but the fragile systems they're forced to use.
So we built a better one.
Baseline is our answer to the constant threat of zero. A stronger foundation for the next generation of onchain economies, where great projects have the support they need to achieve their full potential.
Come check us out at [baseline.markets](https://www.baseline.markets/) or talk with us on [Discord](https://discord.gg/baseline). Learn more in our [docs](https://www.baseline.markets/docs).
---
# The Evolution of Baseline (https://www.baseline.markets/blog/evolution-of-baseline)
Date: 2026-04-09
Author: Bonnie Boo
When we set out to build a token with a guaranteed floor price, we started where everyone starts: Uniswap. Take the x\*y=k formula, manage the liquidity positions well enough, and enforce a floor on top.
This is the story of how we got here. Three versions, two chains, eight audits, and a fundamental rethink of how on-chain liquidity should work. It's also the first article in a series about what floor-backed tokens actually are, how they work, and why they're about to change how tokens are issued.
## What "floor-backed" actually means
A floor-backed token has a minimum redemption price that is enforced on-chain, backed by real reserves, and mathematically guaranteed to never decrease. Three conditions have to hold simultaneously:
* The floor must be backed by real liquidity. The reserves must be locked in smart contracts, always available for redemption.
* Any holder, at any time, must be able to sell at or above the floor price.
* The floor must only go up.
Satisfying all three at once is a mechanism design no existing AMM was built to solve.
Constant product pools (x\*y=k pools), pioneered by Uniswap, have no concept of circulating supply. The formula only tracks the token balance inside the pool, not the total supply in existence. The pool literally cannot tell a token's market cap because it's not part of the equation.
This creates cascading problems for anyone deploying token liquidity. The initial ratio of tokens to reserves permanently determines price sensitivity, liquidity depth, and supply distribution for all future states of the pool. A minor difference in that ratio has massive consequences as supply expands and contracts along the curve.
The math breaks entirely when the pool holds more than half the total supply. The TVL of the pool becomes more valuable than the entire FDV of the token, violating all financial rationality. This is how \$SLERF ended up with 75,000 SOL of permanently inaccessible capital.
The pool was working exactly as designed. The problem is bigger than any single pool. Tokens built on x\*y=k are broken by default. Value leaks out like water through a leaky bucket: to arbitrageurs, to mercenary LPs, to dead capital sitting in unreachable price ranges. The industry has spent years building increasingly clever ways to slow the bleed. Ve(3,3). Concentrated liquidity. On-chain market making for token issuers. None of them fix the crack. They just catch some of the water.
85% of tokens launched in 2025 ended negative. Only 9% that dropped in week one ever recovered. The damage is baked into the curve before the token even hits the chart.
## Protocol Owned Liquidity
OlympusDAO pioneered the idea that protocols should own their own liquidity. We agreed.
But OHM's floor was implicit, not programmatic. There was no smart contract enforcing a minimum redemption price. The "backing per OHM" metric looked like a floor on a dashboard, but holders couldn't redeem at that price on-chain. When sentiment turned, the price crashed well below backing.
That's where Baseline started.
## The Baseline evolution
We took that lesson and started building. What followed was three protocol versions, each one revealing a deeper truth about what floor-backed liquidity requires.
#### V1: The experiment (Blast, 2024)
The first Baseline token launched on Blast using Uniswap V3 as the underlying AMM. The thesis: if we manage concentrated liquidity positions intelligently enough, we can enforce a floor and grow it over time.
It worked, partially. The floor held. The BLV grew. But V3's concentrated liquidity ranges meant value accumulated slowly. Capital got stuck in ranges that weren't actively serving the market.
#### V2: Different liquidity, same curve
V2 iterated on liquidity management with new range strategies and the Afterburner, a randomized leveraged buyback-and-burn. Capital efficiency improved. But no matter how sophisticated the liquidity management layer, the fundamental behavior of constant product doesn't change. It was still designed to maintain balanced exposure between two external assets, not to form capital and grow a floor price.
#### V3: Confirmation (Base)
V3 was the cleanest implementation of Baseline on a constant product curve. Running it in production confirmed what we'd been circling: the curve was the bottleneck. Not the parameters. Not the ranges. Not the chain.
The constant product formula harvests fees from volatility, stays balanced, and treats all flow symmetrically. We needed a curve that does the opposite: accumulate value asymmetrically, price based on circulating supply, and budget reserves to buy back every token in existence.
## Mercury: a new curve for a new era
Mercury is not an optimization of x\*y=k. It's a different equation for a different purpose.
```
y = K · (x/c)² + BLV · c
```
The critical variable is `c`: circulating supply. For the first time, the curve knows how many tokens are held outside the pool and prices accordingly.
Price scales with distribution. What makes a token valuable under Mercury is the ratio of tokens being held versus tokens that have been sold back. When the entire supply is sold back into the pool, Mercury uses all available reserves to buy out every remaining token. Each token's value decomposes into a Baseline Value that holds constant regardless of circulation, and a premium that scales quadratically with demand. Strong demand means trading at multiples above BLV. Full unwind means the price returns to the floor. Mercury adapts across the entire token lifecycle. The pool becomes an asset that improves itself over time, not a liability that needs constant management.
## What is a Baseline Token
* The token owns and manages its liquidity on-chain, 24/7.
* Fees flow back into growing the floor, funding staking rewards, and strengthening reserves. The floor goes up because the mechanism captures trading activity and redirects it into backing.
* Zero-liquidation lending. BLV can never decrease, so holders borrow against it at 0% interest with no liquidation risk and no oracles. Capital unlocked without selling.
## The data
We replayed \$GAME's entire trade history, over 980,000 trades on Aerodrome, through a simulated Baseline pool. Same trades, same timing, different curve.
* **Price:** +59.6% higher from identical trade flow.
* **Liquidity growth:** +267.7% more reserves backing each circulating token.
* **Supply control:** +200.5% more tokens pulled out of circulation.
* **Backing:** +21% growth in guaranteed floor price.
* **Fees:** +81.1% more collected in trading fees.
Other simulation reports: [https://sim.baseline.markets/](https://sim.baseline.markets/)
## Why this matters now
Mercury fixes the curve. And when you fix the curve, you fix a lot of things in crypto.
Every version taught us something. V1 proved the floor could hold. V2 proved liquidity management alone wasn't enough. V3 proved the curve was the bottleneck. Mercury is the answer.
---
# Mercury: A New Curve Primitive For On-chain Token Liquidity (https://www.baseline.markets/blog/mercury-curve-primitive)
Date: 2026-04-04
Author: FullyAllocated
Since the beginning of DeFi, almost every token's on-chain liquidity has been determined by a single liquidity curve, the constant product invariant x\*y=K. In my last article [New Curve, New Era](/blog/new-curve-new-era), I discussed how x\*y=K is an ineffective curve for on-chain token liquidity, and why a new curve needs to be specifically designed to serve this use case.
In this article I will introduce Baseline Mercury, explore the mathematical properties behind liquidity curves, and show you why Mercury's invariant is especially suited for on-chain token liquidity. I believe Mercury will enable a new era for native on-chain asset issuance, and by the end of the article, you will too.
Let's begin.
## There's No Such Thing as a Perfect Curve
In a vacuum, no liquidity curve is inherently better than another. Saying that is like saying that a screwdriver is better than a hammer: it doesn't make sense because they are useful in different situations and meant to serve different purposes.
The same applies to liquidity curves. When I say that the x\*y=K curve is ineffective, I don't mean that there is anything inherently wrong with the equation. I just mean that the specific properties defined by the curve are not useful or desirable for projects that need on-chain liquidity for their tokens.
To understand why, it's necessary to first understand what a liquidity curve is. A curve simply defines a relationship between how the balances of a pool's inventory—its tokens and reserves—change relative to each other across a price spectrum. This can be more intuitively understood from the perspective of an order book: a curve dictates how concentrated orders are at various levels within the book, and how fast the sizes of those orders shrink or grow based on the price.
Every curve has different conditions where it performs better or worse than others. A curve that sells tokens conservatively outperforms a curve that sells them aggressively in a market where the token price increases. The same curve underperforms if the price ends up decreasing instead. To visualize this effect, here are three different invariant curves and how they perform in response to the same price changes:
As such, when evaluating curves, it's critical to understand the choices and preferences on inventory implied by the invariant, and more importantly, what market structure and outcomes the curve is intending to optimize for.
## The Fallacy of General Purpose
This idea is best illustrated by the stableswap invariant, a specialized curve for stablecoin liquidity. In the stableswap invariant, a large amount of pool reserves and tokens can be exchanged without changing price too much, resulting in the vast majority of its liquidity concentrated around a single point. This makes the stableswap invariant a particularly good curve for tokens who expect to stay \$1.00 forever, and horrible for everything else.
For natively issued tokens, the only curve that exists for on-chain liquidity is the constant product invariant x\*y=K. This curve ensures that an equal ratio of tokens and reserves is preserved regardless of price movement, providing even liquidity across every conceivable price. Many people conflate the price agnostic property of the curve with the idea that it is a general purpose liquidity solution, but this could not be further from the truth.
As we established in the outset, each curve performs better under a specific scenario, and x\*y=K is no exception. Constant product liquidity works well under two conditions: the first is when the liquidity pool is not responsible for price discovery, and the second is when the majority of the liquidity belongs outside of the pool. This makes it a great curve to maintain balanced exposure to assets that have already undergone significant price discovery like ETH or BTC.
However, this makes it a horrible curve for projects deploying their own token liquidity!
The constant product invariant is awful at price discovery because that's not what it's designed to do: the curve is designed to respond to external price changes in order to maintain the balance of its internal inventory, not to determine the fair price of a token based on the ratio of available assets in the pool.
The initial ratio of tokens to reserves deposited in the pool permanently determines price sensitivity, liquidity depth, and supply distribution for all possible future iterations of the pool. A minor difference in this ratio has massive cascading effects for how price changes and liquidity grows at different token market caps as the supply expands and contracts along the curve.
The clearest example of this comes from the fact that the constant product equation breaks when the liquidity pool owns more than half of a token's total supply. Mathematically speaking:
In plain english, this means that when a pool owns more than half the total supply of a token, the TVL of the pool's liquidity becomes more valuable than the entire FDV of the underlying token, violating all financial rationality.
It's how you end up with things like this:
I will never not think about \$SLERF. Rent free forever.
Or this:
So now you know how it works!
## The Deployer's Demise
The deeper insight is that the x\*y=K equation has no concept about a token's supply at all. The invariant is based on the token supply in the pool, not the total supply in existence. That's why the curve has no way to tell a token's market cap: it's literally not part of the equation.
This puts the responsibility of pricing the asset, designing the liquidity profile, and distributing the supply squarely on the deployer. The problem is, as we've already determined, "good liquidity" and "price volatility" at one market cap isn't guaranteed at another. There's no single pool configuration that adapts to all possible future states—it's an impossible task. At some point, these pools will break for one reason or another.
I firmly believe that this is a major reason, if not the primary reason, why crypto so far has been a failed experiment. I believe it's why DeFi "failed", why every launchpad failed, why HIP-2 failed (even Hyperliquid couldn't make it work), why tokens only launch on CEXs, why every chart looks the same, and why everyone who launches a token eventually gets labeled a scammer, grifter, or failure.
The single misconception that this "general purpose" curve is sufficient to deploy on-chain liquidity with has probably set the industry back decades of time and billions of capital.
But in a way it also makes me extremely bullish, because I think if we can fix the curve, we'll fix a lot of things in crypto. That's why, despite watching the industry burn down in a giant dumpster fire over the last few years, despite massive amounts of talent pivoting to AI, and despite the general loss of faith, money and vibes, the team at [@BaselineMarkets](https://x.com/BaselineMarkets) never really stopped pushing on liquidity innovation.
And finally, after years of development, we finally have something to present: a new curve specially made to solve on-chain liquidity for tokens.
We're calling it Mercury, and it looks like this:
$y = K \cdot (cx)^2 + BLV \cdot c$
## Different Assumptions, Different Outcomes
Mercury is an invariant curve designed for the sole purpose of defining a liquidity structure around a token's circulating supply, rather than the internal balances of the pool. The equation uses a new input, c, which represents the total supply of tokens held outside the pool, to establish a proper accounting for liquidity utilization around every possible state of circulation.
By doing so, price scales naturally based on the degree of supply distribution: what makes a token valuable is based on the ratio of tokens that want to be held versus the tokens that have already been dumped. This allows Mercury's curve to provide smoother price discovery and deeper liquidity profile across the entire lifecycle of the token, offering higher capital utilization and efficiency throughout.
This becomes especially relevant when the pool holds a larger portion of the total supply in two ways. First, regardless of how many tokens sit in the liquidity pool, the pool won't feel "too thick". Upward price volatility is not suppressed by a dense token supply in the pool and prevents tokens from being easily acquired from the pool at low prices. This helps prevent against "bundling", or supply cornering, at low points on the curve.
Second, there is no leftover capital when the entire supply is sold into the pool. Mercury knows when there are no more tokens left to buy, and can therefore budget accordingly to ensure it uses all of its available capital to buy out all remaining tokens in circulation. This also allows Mercury to sustain higher prices along all points on the curve, since no idle capital sits in unreachable price ranges.
Another unique thing about the Mercury equation is the value decomposition of each token. Unlike x\*y=K, which describes a singular relationship between the two balances of the pool, Mercury's curve is actually two separate pricing curves added together, with each serving a different purpose in the system.
The first price component is a Baseline Value (BLV) for each token in circulation. This value stays the same no matter how many or few tokens are in the market, forming a price support for the market that sets the foundation for its valuation. The second price component is the premium value, which scales quadratically for each additional token in circulation. This describes the additional value on top of the baseline, ensuring price growth as the marginal demand for tokens increases.
Together, this combination supports healthy token price and liquidity for all market conditions. When demand is strong and the overall supply is widely distributed into the market, the token becomes extremely valuable, trading at multiples above its baseline. In periods of lower circulation, the premium compresses and the token trades closer to its BLV. In a full market unwind scenario, the premium drops to zero, and the price of the token returns to its baseline price.
What this means is that project founders and token deployers finally have a liquidity curve that automatically adapts to the appropriate market conditions without needing to worry about initial liquidity configurations. They finally have a liquidity pool that proactively improves itself over time, mathematically optimized to drive long-term value accrual to every single token in circulation. They finally have a liquidity solution that they can view as an asset, rather than a liability.
They finally have a future. And that future begins with Mercury.
To learn more, view our [docs](https://www.baseline.markets/docs).
To see the curves in action yourself, check out the Baseline Simulator:
---
# New Curve, New Era (https://www.baseline.markets/blog/new-curve-new-era)
Date: 2026-03-23
Author: FullyAllocated
For anyone in crypto who has ever traded a token, there always comes a point where you ask: "why does everything I buy always go to zero?"
Governance tokens. Utility tokens. Memecoins. DeFi. Gaming. Fractionalized NFTs. Staking. Restaking. Flywheels. Taxes. Buybacks. It doesn't matter.
It's easy to write off everyone in crypto as greedy, scammy, and extractive, but there are also plenty of well intentioned founders who've launched tokens and failed too. Enough, at least, to investigate if there is a deeper reason why launching a successful token is harder than it seems.
## The Tragedy of Heaven DEX
There are countless stories, but one of the more memorable examples from this past cycle was Heaven/\$LIGHT. They stood out to me because it was clear from their communications that they were thoughtful, well-intentioned, long-term players looking to change the game. They didn't seem like the kind of team to cash out from a 'flash in the pan' moment, yet there's nothing that distinguishes its chart from a bonafide scam.
Their post-mortem had some interesting clues:
In it, they correctly identified the causes that led to their ultimate demise: improved trading tooling, sharper adversarial flow, and the curve quickly becoming "uninhabitable."
But this framing misses the most important detail. In the post, they blame the lack of innovation around the bonding curve and the evolution of bot tooling, pointing to external factors around the liquidity pool. It's a classic case of addressing the symptoms while ignoring the root cause.
In reality, the issue isn't the bots, the tooling, or the launch conditions. While they certainly don't help, no one showed up just to ruin Heaven's party. They are just the consequence of an easily exploitable system. The curve didn't decide to suddenly become uninhabitable; in fact, it was behaving exactly as intended.
## The More Things Change, the More they Stay the Same
Throughout the years, despite the many launchpads conceived to "fix tokens", nothing has stuck as a permanent solution. This is because they all focus on modifying the extrinsic conditions and incentives around the liquidity pool while leaving the underlying economics of the swap untouched: the constant product curve, `x*y=k`.
Traditional market makers are designed to harvest fees from volatility. Their entire model is built around having a balanced inventory so they can always buy when traders sell, and sell when traders buy, extracting a spread in both directions. They don't care about long-term value accrual or price appreciation of the token, only about their PnL.
Constant-product liquidity is a naive attempt to approximate this behavior: it assumes the pool should remain balanced and treats all flow as symmetrical volatility because that's what a neutrality-oriented, extractive system would do. This works fine for pools sitting between two external assets—something like ETH/BTC—where the LP is indifferent to the underlying inventory, and the pool is not responsible for being the primary venue for price discovery.
But that logic doesn't translate cleanly when the liquidity is deployed by a project for its own token. In that context, the pool isn't a neutral participant: the liquidity exists to advance the long-term economic interests of everyone involved. It's there to support capital formation around the project, align incentives between participants, and help sustain the wealth effect that holders are collectively building toward.
If the objectives are different, the behavior should be too. **Until these fundamental assumptions about the liquidity curve are changed, nothing will change.** This is why Baseline is different: it's not about "more features" or "fancier math".
It's about changing the meaning of what it means to be an AMM. Baseline produces different outcomes because Baseline is optimizing for different outcomes.
## It's not a Feature, It's a Bug
Let me illustrate a simple token launch scenario to demonstrate how `x*y=k` falls short. Say you are launching a token with 1M total supply. You sell 50% of the supply in a presale or bonding curve, raising 50K USDC from your community, and pairing it with 100K tokens from the treasury into a liquidity pool. Then you lock the LP to reassure the community that the liquidity is permanent. Sounds good, right?
On the contrary: you have effectively just lit 10% of the funds (\$5,000) on fire.
How do we know? We can simulate how many reserves would be left if the entire supply was dumped into the liquidity pool:
```
k = x (100,000 tokens) * y (50,000 usdc)
x'= 1,000,000 tokens (the entire supply)
y' = k / x' = 5,000 usdc
```
This leftover capital is completely untouched by the market throughout the entire lifecycle of the pool. It simply sits there, compounding with each trade, but remains permanently inaccessible to anyone actually trading the token. The more it grows, the more inefficient it becomes.
At the extreme, these losses can extend to absurd amounts. Remember [\$SLERF](https://dexscreener.com/solana/slerf)? When the dev first launched, he 'accidentally' burned the liquidity, making it immutable forever. However, the liquidity was so thick that most of the funds in liquidity were unusable. Based on [dexscreener](https://dexscreener.com/solana/slerf) and [solscan](https://solscan.io), the unused liquidity today amounts to around 75,000 SOL, **or almost 7 million dollars of completely wasted capital.**
You might be wondering why this happens. Why doesn't the curve know that it's wasting money? Why is it providing liquidity at prices that are impossible to reach, to buy tokens that never existed in the first place?
Believe or not, this is by design. There's nothing in the `x*y=k` equation that provides the context for the total token supply, so by definition, constant product pools have no idea how many tokens they will need to buy. But this exposes an even deeper problem: **without awareness of supply, they don't know the underlying valuations of the assets being swapped in their pools.**
The implications of this are scary to consider. The vast majority of on-chain trading is being facilitated by pools that are completely oblivious to the markets they are providing liquidity for. These pools blindly buy and sell tokens based on what's available in their own pools, unaware of how those trades are impacting the broader market as a result.
Ultimately, it's clear constant product liquidity pools are inefficient at best and debilitating at worse for token launches. At Baseline, we realized if we truly wanted to solve the problem once and for all, we needed to take a entirely different approach. We needed to unlearn everything we knew about on-chain liquidity, how it works, and what it's used for.
## Inverting the Premise
The premise of Baseline's liquidity curve starts with a simple question: what if we've been looking at the liquidity pool the wrong way?
Whether the pool acknowledges it or not, every pool accumulates an average cost basis based on the aggregate swaps in the pool. As a natural consequence, the pool builds a running profit and loss based on the total volume of units sold and purchased and the average prices which they are executed.
Moreover, these two volumes rarely match 1:1, which means the pool is sitting on an open position that represents the current delta in the market's flow, as well as the aggregate value of the unrealized gains or losses of the market. Given this, we decided to approach the liquidity pool not as a yield optimization problem, but instead as market position with its own cost basis and PnL.
The key insight here is what this PnL represents. Since the pool is the counterparty for every trade, the pool's position is the inverse position of all the traders on average. This means that when the pool has a large unrealized gain on its position, all of the traders are on average down. Conversely, when the pool is sitting on a large unrealized loss, the traders are on average up.
This begs the question: if the pool only makes money when traders lose, should the objective of the liquidity even be making money in the first place? How would things look if liquidity pools were designed to lose as much money as possible over a sustained time horizon, in order to subsidize the maximum unrealized PnL possible for all its holders?
While it sounds ridiculous, the critical implementation detail is in how it loses money. If a pool loses money by setting arbitrarily high prices, the first sellers would drain all of the liquidity leaving the rest of the holders empty handed. Rather, the pool needs to be strategically unprofitable—by first making a profit from trading spreads in the short term, and then channeling those profits back into upward price appreciation by buying tokens at higher and higher prices, indefinitely.
This is the driving philosophy behind Baseline's curve. We set out to build a liquidity system that is more costly to short term traders, in order to utilize the extra capital to generate better long-term outcomes for everyone else. We've modified the core rules of the liquidity structure to create entirely new game theory around liquidity pools: one with better aligned incentives, more intelligent liquidity accumulation, and better overall price performance.
## Climbing Out of the Well
Once upon a time, there lived a young frog at the bottom of a well. He had been there all his life and was very comfortable with his surroundings. As he looked up, he enjoyed his very small view of the sky. One day, his cousin came to visit from the outside world and asked the young frog why he had never ventured out of the well. The young frog replied, "I don't need to. I am quite comfortable here. Besides, the sky is so very small, there is nothing out there for me to see." His cousin pleaded with him for a long time and finally convinced the young frog to hop up out of the well. As he reached the midway point toward the top of the well, the young frog looked up and saw the sky broaden. He became fascinated and at the same time nervous and hesitant. His cousin continued to plead with him until he finally reached the top of the well. He was speechless as he gazed upon the vast sky in all directions. He could see trees and meadows and a beautiful pond. "I never knew how much beauty existed outside of the well," he exclaimed.
When I was a kid, I learned about an ancient Chinese parable called "井底之蛙", which translates to "The Frog at the Bottom of the Well". The frog, having lived its entire life in a well, has a limited perspective of the world, unable to grasp the vastness of its possibilities because it can only see the sky as a small circle from where it's looking.
Today, crypto as an industry is sitting at the bottom of the well. Everything we've seen about tokens and liquidity is but a small slice of the world of possibilities. Every time the "next big thing" inevitably goes to zero, we resign ourselves to the fact that this industry is a sham, tokens are worthless, and playing is loser's game over the long term. It further reinforces our learned helplessness that nothing actually works, and nothing ever will.
Like the frog in the parable, we've become complacent with what we have, content with the small blue circle we see called the sky.
But I've never seen it this way. I got into crypto because of what I knew it could be: a way to rebuild the global economy from the ground up and provide a better means for economic mobility for humanity, and the endless wealth opportunities that arise as a result. Call me naive, but I never lost the vision. I've gotten a glimpse the world beyond, and damn is it beautiful.
After years of building, failing, and persisting, I feel like we've finally created something that can help us all see it too.
And once we leave the well, we're never going back.
---
# Decentralized to Desperate: Why Builders Have Given Up on AMMs (https://www.baseline.markets/blog/why-builders-have-given-up-on-amms)
Date: 2025-06-24
Author: Baseline Team
Automated Market Makers (AMMs) are a cornerstone of DeFi. With a few clicks, anyone can provide liquidity for a token, creating a permissionless market in a way that was never possible before. It's a simple innovation that unlocked liquidity for millions of assets, fueling the explosive growth of onchain markets.
For builders, they seem like a great solution for bootstrapping liquidity. Yet they have critical flaws that impact tokens at every stage of their lifecycle. In this article, we will briefly go over some of the issues surrounding the use of AMMs for projects, the most common alternative, and what we believe is missing.
## X\*Y=K, a Blessing and a Curse
The first and most recognized model is the Constant Product Market Maker (CPAMM), famously represented by the formula x\*y=k and first implemented by Uniswap in 2018, and gaining widespread traction around 2020.
This design's beauty is its simplicity and elegance; it is easy to understand, and it just works. However, this same simplicity is the source of significant, persistent problems.
For all their benefits, CPAMMs create a challenging environment for both liquidity providers (LPs) and traders.
For LPs, the primary issues are **Impermanent Loss (IL)** and **Loss-Versus-Rebalancing (LVR)**. Impermanent Loss is the opportunity cost LPs suffer when the price of the assets in a pool diverges—they often would have been better off just holding the tokens. LVR is a more insidious problem; it's the systematic profit extracted from LPs by arbitrageurs who are always faster and better informed, effectively bleeding value from the pool.
For traders, the main threat is **MEV (Maximal Extractable Value)**, most commonly seen in the form of "sandwich attacks." A trader's swap is targeted by a bot that places a large order right before it and an opposite order right after, artificially inflating the price the trader pays and pocketing the difference.
Most importantly, CPAMMs are highly dependent on the amount of liquidity in their pools. Pools with low liquidity are notoriously easy for whales to manipulate, causing wild price swings. The common solution is to provide high-yield liquidity rewards for LPs, but this often is an additional cost and complexity for projects. It attracts mercenary capital that provides liquidity only for the rewards and vanishes the moment they dry up, leaving projects in a worse position.
## Concentrated Liquidity
In 2021, Uniswap V3 introduced the Concentrated Liquidity AMM (CLAMM). This model allows LPs to provide liquidity within specific price ranges, promising greater capital efficiency and better control over the risk LPs take.
For high-volume pairs like ETH/USDC, CLAMMs have been a major step forward. However, they are not a silver bullet. They still suffer from LVR and MEV issues, and their increased flexibility also comes with its own challenges. Managing a CLAMM position is significantly more complex, requiring active monitoring and adjustments.
This complexity makes CLAMMs impractical for the long tail of smaller, less liquid tokens. For these assets, liquidity becomes fragmented and difficult to manage. It's no surprise that even four years after their introduction, the total value locked (TVL) in simple CPAMMs still rivals, and in many cases exceeds, that of their more complex successors.
## The Retreat Off-Chain
Frustrated with the trade-offs of onchain AMMs, many projects have turned to the traditional solution of utilizing private market makers. These solutions offer better pricing for traders but come at a steep cost, often requiring huge incentives for the MMs. This comes in the form of token loans and extremely disadvantageous option structures.
It's not that these MMs are all evil or extractive. The process of providing liquidity for new tokens is extremely risky, and MMs are profit-seeking businesses who must ensure they can make their profits. In addition, there have been many cases of market makers wrecking token performance and being caught in clearly manipulative practices. The truth is, professional MMs require a high amount of trust to act in good faith.
This leaves project founders in a difficult position. To bootstrap liquidity, a critical step for any new token, they must make a huge tradeoff:
* Risk manipulation and unsustainable incentives on a simple AMM.
* Struggle with the complexity and ineffectiveness of a CLAMM.
* Navigate the world of professional market makers before they're ready, forcing them to create potentially disadvantageous deals to secure their liquidity.
## What's Missing?
A clear gap exists in the market. The current landscape serves high-volume, blue-chip assets well, but it fails the very innovators and builders that push the crypto space forward. These projects need a way to build sustainable, efficient liquidity without becoming market makers themselves or sacrificing the benefits of decentralization.
In a space defined by innovation and experimentation, the next evolution of AMMs must be designed for this underserved segment. The liquidity problem for new and growing projects is waiting for a real solution.
[Baseline](https://x.com/BaselineMarkets) is designed from first principles around the problems outlined above. We are crypto natives, believing that onchain, programmable liquidity via AMMs can solve these issues. The first step is identifying the problem.
Stay tuned for more.
---
# Your Token Is Leaking Value (https://www.baseline.markets/blog/your-token-is-leaking-value)
Date: 2026-02-27
Author: Baseline Team
Baseline built an AMM where tokens own their liquidity and retain value over time. Using \$GAME's historical trade data as a benchmark, we simulated how a token would perform if liquidity was owned instead of rented from external LPs. The results were hard to ignore:
Better price performance, stronger reserve backing, healthier supply dynamics, and improved value capture.
## The simulation
\$GAME is an AI agent ([@GAME\_Virtuals](https://x.com/GAME_Virtuals)) built on [@virtuals\_io](https://x.com/virtuals_io) whose main liquidity pool is on Aerodrome.
We replayed \$GAME's entire trade history (over 980K trades) through a Baseline pool. Here's what we found:
* **Price:** **+59.6%** higher from identical trade flow
* **Liquidity growth:** **+267.7%** more reserves backing each circulating token
* **Supply control:** **+200.5%** more tokens pulled out of circulation
* **Backing:** **+21%** growth in guaranteed floor price
* **Fees:** **+81.1%** more collected in trading fees without impacting tradeability
## Where traditional pools fail
Traditional liquidity pools (such as Uniswap and Aerodrome) quote prices using pool inventory and without considering circulating supply. This creates a mismatch between the price and the liquidity supporting that price.
Baseline's pool ended with +59.6% higher price than the standard pool.
Traditional pools are reactive to market flows. Reserves per token thin out during expansion and rebuild too slowly during contraction, leaving weaker support behind each token.
Baseline ended with 267.7% more reserves per circulating token, meaning more liquidity backing the float.
Traditional pools can't distinguish between tokens in the pool and tokens floating in the market.
Baseline quotes based on available float, absorbing 200.5% more tokens and leaving less supply to act as future sell pressure.
Said another way, Baseline was able to **reduce floating supply by 33.5%**.
Traditional pools have no concept of a floor: the only value guaranteed is zero. Baseline channels a portion of every trade into **a guaranteed floor that grew 21%** over the simulation. When backing grows, downside compresses and the token feels safer to hold.
Traditional pools apply static fees with no consideration for market conditions. Mercury keeps spreads competitive while dynamically shifting fees based on market premium, **generating +81% more surplus**.
Note that while the simulation looks purely at pool performance, Baseline tokens offer far more in utility including trading fee capture, staking, borrowing, and leverage, all of which generate activity that flows back into the token.
## Why this matters
Your token is leaking value because the onchain liquidity pools (Uniswap, Aerodrome, etc) were never designed to retain it. When tokens own their liquidity, they stop acting like liabilities and start compounding like assets.
If you're launching a token or running an existing one that's bleeding value, we can run simulations and show you the difference. Drop into our [Discord](https://discord.gg/baseline) or check out our [docs](https://www.baseline.markets/docs).