Exploring the combination of intent and on-chain derivatives: how to shape DeFi 3.0?

Translation: Vernacular Blockchain

Intention-driven applications will shape decentralized finance (DeFi) 3.0, and if you haven’t realized it yet, it’s probably because you haven’t understood what intent can unleash potential.

I will publish this article to tell you about decentralized intentions:

It is impossible to explore every possible use case released by intentions, because this requires countless threads. I want to keep it as compact as possible.

I want to focus on a specific area of ​​finance, where trillions of dollars are moved every year in the traditional financial system, and some estimates even reach quadrillions of dollars.

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 each center This is a model being used by trading platforms such as Binance, with the first DeFi implementation being done by @dYdX.

The reason every trading platform uses order books is because it is the best infrastructure model they can use. But if that's true, why did dozens of other teams full of smart people decide to choose another path?

This is because the order book requires sophisticated market makers to actively provide liquidity and rapid order matching. While the former is easier to achieve, the latter is sometimes impossible. Imagine building an order book with a 12 second block time on the Ethereum mainnet.

This is why many teams have decided to migrate their matching engines off-chain. dYdX V3, Aevo, RabbitX, etc. are all good product examples, but their amazing speed comes at the cost of decentralization.

Some projects have successfully built fully on-chain order books by using alternative virtual machines (altVMs). The best example is Hyperliquid which I really like and the V4 version of the giant dYdX.

2. Liquidity Provider (LP)-based model

This is a huge 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 the asset price falling, 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 model

Although like @DriftProtocol and @perpprotocol Perpetual contracts like V1 use AMM and vAMM structures, but they are now considered obsolete models.

Interestingly, they are now being used in hybrid models.

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

@DriftProtocol is similar, but it even has a third source of liquidity: they call it JIT liquidity.

JIT stands for Just-In-Time, which is a Dutch auction model.

This approach is very interesting because it is similar to the mechanism used by intent-driven protocols. For example, UniswapX and 1Inch Fusion utilize a Dutch auction model in order to allow solvers to satisfy intent efficiently.

4. Aggregators

They aggregate orders from multiple decentralized trading platforms (dexes) and provide the best of all integrated trading venues price. They can also split transactions across multiple platforms.

They usually also have their own fund pool.

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

4) Solver Model (aka intent-driven)

Broadly speaking, we view the solver (aka filler/relayer) as a financially motivated chain external proxy to satisfy the user's intent.

In perpetual contracts, the solver is the market maker who assumes your opposite position.

In the derivatives world, solver implementation is still very immature. However, these models have seen significant adoption when it comes to the rest of the cryptocurrency space.

You can see their growth below:

#One of the pioneers of this model is @DriftProtocol, their V2 version went live at the end of 2022, and The previously mentioned JIT liquidity is introduced.

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, and third-party teams can utilize this infrastructure 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) capital 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 field is really fascinating, and it may truly become the basic element of 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 intentions.

3) The threshold for deploying and operating solvers is relatively 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 permissionlessness and self-custody.

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

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