How Intent-Driven Shape DeFi 3.0

Intermediate7/11/2024, 10:33:37 AM
Intent-driven applications will be an important component of Decentralized Finance (DeFi) 3.0. This article introduces the potential of intent-driven applications and emphasizes the need to be concise when exploring all possible use cases. It then delves into several popular current decentralized trading models: the Central Limit Order Book (CLOB) model, the Liquidity Provider (LP) model, the Automated Market Maker (AMM) and virtual Automated Market Maker (vAMM) models, and hybrid models. Each model has its own advantages and disadvantages. The article also discusses the aggregator model and the solver model (intent-driven), noting that the solver model's application in the derivatives field is still immature but has made significant progress in other cryptocurrency areas. Finally, the article summarizes three main challenges in the intent-driven field: solver competition leading to centralization, fragile solver infrastructure for complex intents, and high thresholds for deploying and operating solvers.

Intent-Driven apps will shape DeFi 3.0. If you haven’t realized it yet, it’s because you haven’t grasped the potential that intent can unleash.

In this article, I’ll delve into the world of decentralized intent:

Unraveling every possible use case of intent would be an endless task. I’d like to keep it concise.

I’ll be focus on a specific financial domain that moves trillions of dollars annually in traditional finance, with some estimates reaching tens of trillions.

Before we dive into the future of on-chain derivatives, let’s take a look at the current models and their main trade-offs.

The following is a common classification:

1. CLOB (central limit order matching) model

This is the model being used by every centralized exchange like Binance, with the first DeFi implementation being done by @dYdX.

The reason why every trading platform uses order books is because it is the best infrastructure model they can use. However, if that’s true, why have dozens of other teams opted for different approaches?

This is because the order book requires sophisticated market makers to actively provide liquidity and fast order matching. While the former is relatively easy, the latter can be challenging, especially on Ethereum’s mainnet with its 12-second block times.

This is why many teams have moved their matching engines off-chain. dYdX V3, Aevo, and RabbitX are excellent 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 examples are Hyperliquid and leading project dYdX’s upcoming V4.

2. Liquidity Provider (LP)-Based Model

This is a vast category that contains several sub-models with subtle differences between them. A common feature is that price discovery occurs outside the protocol. They use oracle providers or custom price sources similar to @PythNetwork and @chainlink.

This would be the worst-case scenario because not only would you be affected by a drop in the price of the asset, but you would also have to pay out the profit to the trader. Your capital will be destroyed.

However, there are some advantages.

Since they use oracles to price assets, you can achieve slippage-free trading, which can be very interesting for traders, especially for long-tail assets, and that’s not all. As a DeFi Maxi, one of the features of DeFi that I like is its composability.

Tokens like @GMX_IO’s GLP or @JupiterExchange’s JLP are composable. You can use them as collateral in loans, trades, or in certain leverage strategies. These use cases do not exist in other sustainable decentralized exchange models.

3. AMM (automatic market maker), vAMM (improved automatic market maker) and hybrid models

While perpetual contracts like @Drift Protocol and @perp protocol V1 used AMM and vAMM structures, they’re now considered outdated models.

Interestingly, they’re now being used in hybrid models.

@Vertex_Protocol employs a price/time algorithm: orders will be executed at the best available price, whether from the order book or AMM.

@Drift Protocol takes a similar approach but adds a third liquidity source: JIT liquidity, which is a Dutch auction model.

This method is intriguing as it resembles the mechanism used by intent-driven protocols. For instance, UniswapX and 1Inch Fusion leverage Dutch auction models to allow solvers to effectively execute intents.

4. Aggregator

These platforms aggregate orders from multiple decentralized exchanges (DEXs) and provide the best price across all integrated venues. They can also split trades across multiple platforms.

They often have their own liquidity pools as well.

Among the aggregators, there is also @vooi_io, who are developing a cross-chain aggregator (EVM + AltVM).

4) Solver model (aka intent-driven)

Broadly, we define solvers (also known as order fillers/relayers) as off-chain, economically motivated agents that aim to fulfill users’ intents.

In perpetual contracts, a solver takes the opposite side of your market maker.

In the derivatives space, solver implementation is still very nascent. However, these models have seen significant adoption in other crypto domains.

You can see their growth below:

One of the pioneers of this model is @DriftProtocol, their V2 version went live in late 2022 and introduced the previously mentioned JIT liquidity.

Another player in this space is @symm_io, which allows bilateral agreements (RFQs) between two parties: traders and solvers.

In this case, the solver is also called a “hedger”. Market makers generally don’t take price risk: if they take a position opposite to yours, they need to hedge that trade elsewhere.

The interesting concept here is that on-chain users trade with off-chain liquidity.

Symmio focuses on building the backend and infrastructure of a sustainable decentralized trading platform, which third-party teams can leverage for development.

@CadenceProtocol is also building a similar system.

@UniDexFinance is a perpetual contract aggregator built on @MoltenL3 and introduces the PrMM (Programmable Market Maker) fund pool.

This is an interesting concept as it allows the creation of programmable pools that are fully customizable to run specific market making strategies.

5. Summary

The intent-driven space is really fascinating and could truly become a foundational element for the next generation of decentralized applications. Despite its strong value proposition, development in this area is still in its early stages. There are three main challenges:

1) Solver competition leads to centralization.

2) Fragile solver infrastructure for complex intents.

3) The threshold for deploying and operating solvers is high.

But one of the main reasons that gives me confidence is that there are some of the smartest people working on these problems. For example: @EverclearOrg; @EnsoFinance; @aori_io; @anoma; @intentessential; @ApertureFinance, etc.

As far as the derivatives decentralized trading platform field is concerned, I think it is at the stage of a revolution of intent:

1) What traders need most is speed and liquidity.

2) Since they are transacting on-chain, they also care about being permissionless and self-custody.

3) A mature intent-driven domain can meet all these needs.

statement:

  1. This article is reproduced from [vernacular blockchain], the copyright belongs to the original author [@Cryptovoxam], if you have any objections to the reprint, please contact the Gate Learn team, and the team will handle it as soon as possible according to relevant procedures.

  2. Disclaimer: The views and opinions expressed in this article represent only the author’s personal views and do not constitute any investment advice.

  3. Other language versions of the article are translated by the Gate Learn team and are not mentioned in Gate.io, the translated article may not be reproduced, distributed or plagiarized.

How Intent-Driven Shape DeFi 3.0

Intermediate7/11/2024, 10:33:37 AM
Intent-driven applications will be an important component of Decentralized Finance (DeFi) 3.0. This article introduces the potential of intent-driven applications and emphasizes the need to be concise when exploring all possible use cases. It then delves into several popular current decentralized trading models: the Central Limit Order Book (CLOB) model, the Liquidity Provider (LP) model, the Automated Market Maker (AMM) and virtual Automated Market Maker (vAMM) models, and hybrid models. Each model has its own advantages and disadvantages. The article also discusses the aggregator model and the solver model (intent-driven), noting that the solver model's application in the derivatives field is still immature but has made significant progress in other cryptocurrency areas. Finally, the article summarizes three main challenges in the intent-driven field: solver competition leading to centralization, fragile solver infrastructure for complex intents, and high thresholds for deploying and operating solvers.

Intent-Driven apps will shape DeFi 3.0. If you haven’t realized it yet, it’s because you haven’t grasped the potential that intent can unleash.

In this article, I’ll delve into the world of decentralized intent:

Unraveling every possible use case of intent would be an endless task. I’d like to keep it concise.

I’ll be focus on a specific financial domain that moves trillions of dollars annually in traditional finance, with some estimates reaching tens of trillions.

Before we dive into the future of on-chain derivatives, let’s take a look at the current models and their main trade-offs.

The following is a common classification:

1. CLOB (central limit order matching) model

This is the model being used by every centralized exchange like Binance, with the first DeFi implementation being done by @dYdX.

The reason why every trading platform uses order books is because it is the best infrastructure model they can use. However, if that’s true, why have dozens of other teams opted for different approaches?

This is because the order book requires sophisticated market makers to actively provide liquidity and fast order matching. While the former is relatively easy, the latter can be challenging, especially on Ethereum’s mainnet with its 12-second block times.

This is why many teams have moved their matching engines off-chain. dYdX V3, Aevo, and RabbitX are excellent 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 examples are Hyperliquid and leading project dYdX’s upcoming V4.

2. Liquidity Provider (LP)-Based Model

This is a vast category that contains several sub-models with subtle differences between them. A common feature is that price discovery occurs outside the protocol. They use oracle providers or custom price sources similar to @PythNetwork and @chainlink.

This would be the worst-case scenario because not only would you be affected by a drop in the price of the asset, but you would also have to pay out the profit to the trader. Your capital will be destroyed.

However, there are some advantages.

Since they use oracles to price assets, you can achieve slippage-free trading, which can be very interesting for traders, especially for long-tail assets, and that’s not all. As a DeFi Maxi, one of the features of DeFi that I like is its composability.

Tokens like @GMX_IO’s GLP or @JupiterExchange’s JLP are composable. You can use them as collateral in loans, trades, or in certain leverage strategies. These use cases do not exist in other sustainable decentralized exchange models.

3. AMM (automatic market maker), vAMM (improved automatic market maker) and hybrid models

While perpetual contracts like @Drift Protocol and @perp protocol V1 used AMM and vAMM structures, they’re now considered outdated models.

Interestingly, they’re now being used in hybrid models.

@Vertex_Protocol employs a price/time algorithm: orders will be executed at the best available price, whether from the order book or AMM.

@Drift Protocol takes a similar approach but adds a third liquidity source: JIT liquidity, which is a Dutch auction model.

This method is intriguing as it resembles the mechanism used by intent-driven protocols. For instance, UniswapX and 1Inch Fusion leverage Dutch auction models to allow solvers to effectively execute intents.

4. Aggregator

These platforms aggregate orders from multiple decentralized exchanges (DEXs) and provide the best price across all integrated venues. They can also split trades across multiple platforms.

They often have their own liquidity pools as well.

Among the aggregators, there is also @vooi_io, who are developing a cross-chain aggregator (EVM + AltVM).

4) Solver model (aka intent-driven)

Broadly, we define solvers (also known as order fillers/relayers) as off-chain, economically motivated agents that aim to fulfill users’ intents.

In perpetual contracts, a solver takes the opposite side of your market maker.

In the derivatives space, solver implementation is still very nascent. However, these models have seen significant adoption in other crypto domains.

You can see their growth below:

One of the pioneers of this model is @DriftProtocol, their V2 version went live in late 2022 and introduced the previously mentioned JIT liquidity.

Another player in this space is @symm_io, which allows bilateral agreements (RFQs) between two parties: traders and solvers.

In this case, the solver is also called a “hedger”. Market makers generally don’t take price risk: if they take a position opposite to yours, they need to hedge that trade elsewhere.

The interesting concept here is that on-chain users trade with off-chain liquidity.

Symmio focuses on building the backend and infrastructure of a sustainable decentralized trading platform, which third-party teams can leverage for development.

@CadenceProtocol is also building a similar system.

@UniDexFinance is a perpetual contract aggregator built on @MoltenL3 and introduces the PrMM (Programmable Market Maker) fund pool.

This is an interesting concept as it allows the creation of programmable pools that are fully customizable to run specific market making strategies.

5. Summary

The intent-driven space is really fascinating and could truly become a foundational element for the next generation of decentralized applications. Despite its strong value proposition, development in this area is still in its early stages. There are three main challenges:

1) Solver competition leads to centralization.

2) Fragile solver infrastructure for complex intents.

3) The threshold for deploying and operating solvers is high.

But one of the main reasons that gives me confidence is that there are some of the smartest people working on these problems. For example: @EverclearOrg; @EnsoFinance; @aori_io; @anoma; @intentessential; @ApertureFinance, etc.

As far as the derivatives decentralized trading platform field is concerned, I think it is at the stage of a revolution of intent:

1) What traders need most is speed and liquidity.

2) Since they are transacting on-chain, they also care about being permissionless and self-custody.

3) A mature intent-driven domain can meet all these needs.

statement:

  1. This article is reproduced from [vernacular blockchain], the copyright belongs to the original author [@Cryptovoxam], if you have any objections to the reprint, please contact the Gate Learn team, and the team will handle it as soon as possible according to relevant procedures.

  2. Disclaimer: The views and opinions expressed in this article represent only the author’s personal views and do not constitute any investment advice.

  3. Other language versions of the article are translated by the Gate Learn team and are not mentioned in Gate.io, the translated article may not be reproduced, distributed or plagiarized.

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