In the 'Future of a Thousand Chains', the obvious thesis is that chain abstraction is the next big frontier and massive problem to be solved. However, in this future world, everyone is missing the bigger picture: What about orderflow?

Chain Abstraction: A Closer Look

Chain abstraction in crypto refers to simplifying the interaction between users and multiple blockchain networks. With numerous blockchains, each with its protocols, assets, and functionalities, chain abstraction aims to make these complexities invisible to the end user. The basic premise is that, in the future, there will be thousands of chains, but the user experience will be so seamless that participants won’t even realize which chain they are interacting with.

For the next phase of crypto, we need to make transfers and value creation/extraction as easy as possible for end users. User experience has always been a challenge for the industry—clunky and difficult. Embedded wallets have allowed a web2-like experience for sign-ups, pushing the needle forward, especially for consumer apps. However, solving the issue of transacting between multiple chains seamlessly will be the next big innovation for adoption. This is where the chain abstraction thesis comes from.

The Other Frontier: Simplification of User Actions by Intents

The next user experience frontier on the front end is the simplification of user actions by intents. Intents allow users to define their desired outcomes for transactions, abstracting away the complexities of blockchain operations. Instead of dealing with intricate steps and technical details, users simply specify what they want to achieve, and the system handles the rest.

The Missing Element: Orderflow

Nevertheless, this thesis is missing an element: orderflow.

The more chains you have and the more easily it is to transact between ecosystems, the more orderflow there is between multiple chains. Orderflow between different blockchains, each with its own protocols, assets, and specific types of transactions and function calls from contracts on-chain, requires optimization. It's a huge opportunity. It's a very challenging one.

Imagine when there are thousands of chains with an even greater number of DApps. And all the liquidity and messaging/composability between DApps and chains is un-siloed. That's billions of capital/liquidity in orderflow. Therefore, there is a need to optimize it all in tandem with the technological advancements in interoperability.

You don't get full chain abstraction without also improving orderflow processing and fulfillment.

Orderflow itself is a slept-on meta and missing from the thesis.

Optimizing Orderflow: The Next Frontier

If we are living in a world with thousands of chains, the problem arises from orderflow and how to best optimize it (broadcast, route, execute). Optimizing routes across chains and incentivizing best execution and capital efficiency is the missing piece in the multi-chain world.

Improving Capital Efficincy: In a world with numerous blockchains, each transaction can involve multiple steps and interactions across different networks. Optimizing orderflow ensures that transactions are processed in the most efficient manner, reducing the time taken to complete transactions. By streamlining the routing and execution of transactions, users experience faster and more reliable services.Reducing Cost: Optimized orderflow can significantly reduce the costs associated with transactions. By ensuring that transactions are routed through the most cost-effective paths and leveraging mechanisms like pay-for-order-flow (PFOF), users can benefit from lower fees. This is particularly important in a multi-chain ecosystem where transaction costs can vary widely between networks, as well as dynamiacally change when demand for block space increases.

Enhancing Liquidity: Effective orderflow optimization can enhance liquidity across multiple chains. By enabling seamless transactions between different blockchains, liquidity is no longer siloed within individual ecosystems. This interconnected liquidity allows for better price discovery, reduced slippage, and more efficient markets. Cross-chain liquidity pools and automated market makers (AMMs) can thrive in such an environment, providing users with deeper liquidity and better trading opportunities.

User Experience: Key Requirements

In this scenario, the focus should be on chain abstraction and optimizing orderflow for users so they can easily transact cross-chain and interact with DApps and protocols.

In this scenario, you want:

• User-Friendly: An intuitive interface where users can specify their desired outcome for a cryptocurrency transaction in simple terms.

• Streamlined: Abstraction of the complexities of cross-domain communication.

• Secure: Security of user funds via a permissionless network of solvers who provide a stake before handling these funds, removing reliance on any centralized entity that can negatively influence users’ goals.

• Optimized: Solvers providing optimal solution routes to users' intents, using cross-domain Coincidence of Wants (CoW) matching whenever possible to maximize returns by eliminating fees otherwise needed to meet users' goals.

• Incentivized: Democratized revenue sharing for participants such as block producers, validators, searchers, and relayers, who are incentivized via competition to perform their roles to the best of their abilities.

Enter The Mantis Framework

The Mantis framework strives to optimize all aspects of the crypto order flow process. Of course, a major way this is accomplished is by having solvers compete to provide solutions to user intents, delivering best execution. However, Mantis further incorporates pay-for-order-flow (PFOF)  and optimizes for cross-chain maximal value extraction (MEV). This provides even greater benefits to all parties involved in the order flow process, including users.

Cross-Domain MEV Extraction on Mantis

The Mantis cross-domain intent settlement framework supports increased opportunities for extracting cross-domain maximal extractible value. MEV in general is the maximal value extractable between one or more blocks, given any arbitrary re-ordering, insertion or censorship of pending or existing transactions (as defined by Obadia et al., 2021). Cross-domain MEV can then be defined as the maximum value that can be captured from arbitrage transactions executed in a specified order across multiple domains.

In the Composable ecosystem specifically, cross-domain MEV is potentiated from cross-chain intent settlement. Composable’s MANTIS receives user transaction intents, which are then picked up by solvers who compete to find the best solution to execute these intents. Once the optimal solution is chosen via a scoring mechanism, the winning solver must then execute upon their proposed solution. A single solution can involve a number of different domains. Searchers can access the orderflow from these solutions not only within each domain but also between domains, thus resulting in cross-domain MEV in a number of forms.

Benefits of this MEV extraction approach for different ecosystem participants are as follows:

• Proposers: These entities propose which transactions to include in the next block by looking at which transactions in the mempool pay the highest priority fee; thus, proposers are able to take advantage of MEV opportunities.

• Searchers: These entities extract MEV by running complex algorithms. On MANTIS, searchers extract MEV from the presence of transactions in pre-processed blocks proposed by proposers.

• Users: A portion of revenues from proposers, searchers, and others can route to users to offset user gas fees (as explained below).

The Mantis On-Chain Pay-for-Order Flow Model

Pay-for-order-flow is a concept that has its origins in traditional finance. In PFOF, a market maker pays a broker for routing their clients’ trades to the market maker. Thus, market makers benefit from increased order flow (and thus increased earnings), while brokers earn money by effectively selling the order flow of their users to market makers. Moreover, clients can benefit from reduced trading costs.

This concept remains essentially the same in the DeFi context: market makers pay order flow originators to route trades to them. Benefits to participants in DeFi PFOF models include:

• Market makers (solvers): On Mantis, market makers can be independent entities or solvers can play a market making role. These parties benefit from increased order flow, resulting in increased earnings

• Orderflow originators: These are protocols that generate user orders (or intents, on Mantis). Such protocols make money from selling order flow to market makers

• Users: End users can have reduced (or even completely eliminated) gas costs on their transactions.

Within the PFOF model we implement on Mantis, gas costs are a dynamic value that is subject to market conditions. This means that users could be able to trade for free, but only in the event that the below incentive equation is positive, and solvers are able to cover user gas fees:

• (+) 0.1% of transfer

• (+) Sale to blockbuilders

• (+) MEV

• (-) Money paid to blockbuilders in the role of searcher

• (-) User’s gas

If not, then users will have a partial gas payment. Solvers can also take out short term loans and use these to cover gas fees, then pay these loans off after the order is executed and they receive their rewards.

Summary

At Mantis, we see MEV and PFOF as complementary, and eventually these mechanisms will become the solution that allows users to transact in a largely fee-less manner. Other Mantis participants also benefit from these MEV and PFOF mechanisms, including orderflow originators, market makers/solvers, searchers, proposers, and searchers. Ultimately, incorporating PFOF and cross-chain MEV extraction into Mantis are just a few of the many ways that the Mantis framework transforms the DeFi orderflow paradigm for the better.