This article explores the ways in which intentions are combined with on-chain derivative products and how this combination is driving the DeFi industry towards the 3.0 stage of development. The article is sourced from @Cryptovoxam and published by Blockchain Plain Language.
Summary:
Constructing Windows for the Web3 Era” Intention-Centric Leading Project dappOS Detailed Explanation
Background:
Why is the new narrative “intention” expected to change blockchain and Web3?
Table of Contents:
What is intention?
CLOB (Central Limit Order Book) Model
LP-based Model
AMM (Automated Market Maker), vAMM (Improved Automated Market Maker), and Hybrid Models
Aggregator
Conclusion
Intention-driven applications will shape DeFi 3.0, and if you haven’t realized this yet, it may be because you haven’t understood the potential that intentions can unleash. This article discusses what decentralized intention is:
Exploring every possible use case that intentions can unleash is impossible as it requires countless narrative executions. I hope to keep the expression as concise as possible. I want to focus on a specific financial sector that moves trillions of dollars annually in the traditional financial system, with some estimates reaching trillions of dollars.
Before we delve into the future of on-chain derivatives, let’s first look at the current models and their main trade-offs.
The following is a common classification:
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This is the model used by every centralized exchange platform (such as Binance), with the first DeFi implementation completed by @dYdX.
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Every exchange platform uses an order book because it is the best infrastructure model they can use. But if this is true, why did dozens of teams full of smart people decide to choose a different path?
This is because order books require complex market makers to actively provide liquidity and fast order matching. While the former is easier to achieve, the latter is sometimes impossible. Imagine building an order book on the Ethereum mainnet with a 12-second block time.
That’s why many teams decided to move the matching engine off-chain. Products like dYdX V3, Aevo, RabbitX, etc., are good examples, but their impressive speed comes at the cost of decentralization.
Some projects have successfully built fully on-chain order books using alternative virtual machines (altVMs). The best example is Hyperliquid, which I really like, and the giant dYdX’s V4 version.
This is a huge category that includes several sub-models with subtle differences between them. A common feature is that price discovery happens off-chain. They use Oracle providers or custom price sources similar to @PythNetwork and @chainlink.
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This would be the worst-case scenario because you not only suffer from asset price declines but also have to pay profits to the traders. Your capital will be destroyed.
However, there are also some advantages.
Since they use oracles to price assets, you can achieve slip-free trading, which can be very interesting for traders, especially for long-tail assets, and that’s not all. As a DeFi Maxi, one feature of DeFi that I like is its composability.
Tokens like GLP from @GMX_IO or JLP from @JupiterExchange are composable. You can use them as collateral in loans, trades, or leverage strategies. These use cases are not present in other sustainable decentralized trading models.
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While perpetual contracts like @DriftProtocol and @perpprotocol V1 use AMM and vAMM structures, they are now considered outdated models. Interestingly, they are now being used in hybrid models.
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@vertex_protocol has a price/time algorithm: orders will be executed at the best available price, whether from the order book or AMM.
Similar to @DriftProtocol, but it even has a third liquidity source: they call it JIT Liquidity.
JIT stands for Just-In-Time, which is a Dutch auction model.
This approach is very interesting because it resembles the mechanism used by intention-driven protocols. For example, UniswapX and 1Inch Fusion use Dutch auction models to efficiently meet intentions.
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They aggregate orders from multiple decentralized exchange platforms (dexes) and provide the best price across all integrated trading venues. They can also split trades across multiple platforms.
They usually have their own liquidity pool.
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In the aggregator space, there is @vooi_io, which is developing a cross-chain aggregator (EVM + AltVM).
4) Solver Model (also known as intention-driven)
Broadly speaking, we consider solvers (also known as fillers / intermediaries) as off-chain agents driven by economic incentives to fulfill user intentions.
In perpetual contracts, solvers act as market makers on the opposite side of your position.
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Implementing solvers in the derivatives space is still very immature. However, when it comes to other cryptocurrency areas, these models have seen significant adoption.
Below you can see their growth:
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One of the pioneers of this model is @DriftProtocol, whose V2 version was launched at the end of 2022, introducing the previously mentioned JIT liquidity.
Another player in this space is @symm_io, which allows for bilateral protocols (RFQ) between two parties: traders and solvers.
In this case, solvers are also known as “hedge funds.” Market makers typically do not bear price risk: if they are opposite to your position, they need to hedge that trade elsewhere.
The interesting concept here is that on-chain users are trading with off-chain liquidity.
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Symmio focuses on building the backend and infrastructure for sustainable decentralized trading platforms, which third-party teams can leverage for development.
@CadenceProtocol is also building a similar system.
@UniDexFinance is a perpetual contract aggregator built on @MoltenL3, introducing PrMM (Programmable Market Maker) liquidity pools.
This is an interesting concept because it allows for the creation of programmable liquidity pools that are fully customizable to execute specific market-making strategies.
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The intention-driven space is truly fascinating and could become a fundamental element of the next generation of decentralized applications. While it has a strong value proposition, the development of this space is still in its early stages. There are three main challenges:
1) Solver competition leads to centralization.
2) Fragile solver infrastructure for complex intentions.
3) Higher barriers to deploying and operating solvers.
But one of the main reasons that gives me confidence is that some of the smartest people are working hard to solve these problems. Such as:@EverclearOrg;@EnsoFinance;@aori_io;@anoma;@intentessential;@ApertureFinance, and so on.
In the field of decentralized derivatives trading platforms, I believe it is in the stage of revolutionizing intentions:
1) Traders need speed and liquidity the most.
2) Because they are trading on-chain, they also care about permissionless and self-custody.
3) A mature intention-driven domain can meet all these needs.
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Related Reports
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