Since Paradigm first introduced the concept of Intent-Centric narrative in 2023 and included it as one of the top ten most watched tracks, over a year has passed. Apart from the star products that garnered attention at ETHCC, there are many project teams that have chosen to quietly work behind the scenes, focusing on product improvement and practical applications.
With the rapid development in the field of AI, particularly in the AI Agent direction, a more crypto-native AI+crypto product concept has emerged, namely AI Agent as a Solver. However, the challenge that remains for everyone is how to organically implement products based on incentive mechanisms rooted in cryptoeconomics.
The recent launch of Optopia’s mainnet may provide the market with a reference to the latest engineering practice combining AI Agent driven by economic incentives and Intent-Centric.
Intent-Centric Architecture Review: Key Engineering Challenges
Since the last time Intent-Centric narrative gained significant exposure in the market, a year has passed. Looking back at the progress in this track over the past year, we delve into analyzing the constraints of engineering practices.
Using relatively abstract language to describe intent, that is, “on-chain users propose goals and a set of constraints, outsourcing the complexity of interacting with the blockchain, ensuring user control over assets and encrypted identities while achieving optimal paths.” The transaction aggregator is an example of a long-running intent, where users propose goals and constraints like “complete trades between A/B with the optimal price for a quantity of X,” and the aggregator is responsible for finding the optimal price routing path in different liquidity pools, simulating the optimal path execution results for users, thus fulfilling the intent.
Based on the description above, a general Intent-Centric architecture is shown in Figure 1, where ATO (Abstracted Transaction Objects), i.e., the user’s intent, is represented. The main roles in the process include Client, Driver, and Solver, each with specific responsibilities:
Client: The frontend that interacts with users, translating user input from natural language into machine language forms, a structured intent description including goals and constraints.
Driver: Playing the most crucial role in the entire intent architecture, including ATO broadcasting to the memory pool, allowing all solvers to initiate their execution process in the memory pool to find the best solution. Simulating and verifying the solutions received from all solvers, conducting off-chain simulations to ensure their validity and security, then publishing the winning solution. Aggregating solutions from different ATOs for a given intent, combining them into a unified execution plan for final implementation.
Solver: The implementer of intent, usually multiple, providing the best target execution path based on the constraints of the intent.
Ever since the concept of Intent was introduced, it has sparked numerous discussions within the industry. Some critics argue that intent-centric leans more towards an abstract expression of product design philosophy, making it challenging to implement in engineering. Furthermore, issues such as the security of user assets, information loss during the translation from natural language to machine language, entry, selection, settlement, and incentive mechanism design for solvers are all challenges that need to be addressed in specific implementations.
Optopia Architecture Analysis: Solution Based on AI Agent
As mentioned earlier, the specific engineering implementation of intent-centric architecture under the current blockchain architecture is challenging, with existing solutions mostly encapsulating a layer above the chain. However, Optopia is the first Ethereum layer2 specifically designed for engineering implementation of intent at the chain level, and it has built an intent-centric publishing framework specifically for the on-chain AI ecosystem.
As shown in Figure 2, from a modular perspective, Optopia is built on the Raas (Rollup as a Service) service of 4everland. Based on the Op stack framework, utilizing decentralized storage solution Arweave as a DA service provider to ensure data persistence and accessibility, it has created a low-cost, efficient, and modular infrastructure ledger, providing a standard framework for AI agents to execute Web3 transactions.
In the intent publishing center framework designed by Optopia as shown in Figure 3, it includes the following key roles:
Intent Publisher: Responsible for creating intent within the intent center and incentivizing AI agents to effectively execute these intents by allocating valuable tokens. Intent refers to actionable goals or tasks that AI agents can undertake.
AI Agent: AI agents interact with the intent center to access and utilize available knowledge to attempt and complete the assigned intents. They receive rewards in the form of reward points upon successfully completing intents, which they then use for reward allocation.
Builder: Builders train and publish knowledge for AI agents to access, learn, and use, playing a crucial role in the AI ecosystem. This process enhances the capabilities of AI agents, with builders receiving incentives based on the share of reward points obtained by AI agents using their knowledge.
$OPAI Token Holders: OPAI holders can lock OPAI tokens and receive voting locked tokens (vlOPAI). By using these tokens for voting, OPAI holders can determine the emission weight of intents within the intent center. This weight, in turn, affects the OPAI rewards that AI agents receive upon completing each intent.
In the general intent execution framework mentioned earlier, Solver is the entity that executes user intents, whether in an on-chain or off-chain environment. Solvers compete to solve user-proposed intents to earn rewards. This model encourages efficiency and innovation, as multiple solvers will attempt to complete user intents in the most effective way.
Optopia further advances this concept through its unique framework. In the Optopia ecosystem, AI agents take on the role of solvers but with deeper integration and encapsulation. This means that AI agents are not just independent entities executing intents; they can also utilize specific knowledge repositories created and optimized by builders to enhance their execution capabilities. If traditional solvers were compared to the previous generation of search engines, only able to execute along predetermined paths, then the replacement by AI agents upgrades them to GPT, capable of more freely intelligent path searches.
Integrating Cryptoeconomics: The Fusion of Incentive Frameworks
Although Optopia has not yet released a more detailed economic model, we can glean insight from its intent publishing center framework. Faced with potential significant disparities in AI Agent execution results and inconsistencies between incentives and goals, the framework introduces the classic ve model into the ecosystem.
The execution flow of the intent publishing center framework is as follows:
Intent Creation and Incentives: Intent publishers create intents within the intent center and allocate valuable tokens to incentivize AI agents to effectively execute these intents.
Knowledge Training and Publishing: Builders train and publish knowledge for AI agents to access, learn, and use. Their incentives are related to the share of reward points obtained by AI agents using their knowledge.
AI Agent Interaction: AI agents interact with the intent center to access intents and utilize their knowledge to attempt and complete the assigned intents.
Reward Allocation: Upon successfully completing intents, AI agents receive reward points, with builders receiving a share of reward points to help allocate intent rewards.
Involvement of $OPAI Holders: $OPAI holders have the opportunity to participate in the governance of the intent center by locking OPAI tokens, receiving vlOPAI, and voting on the emission weight of intents.
First and foremost, the accuracy of AI Agent execution results is crucial for the overall development of the Optopia ecosystem, with a direct impact on the price of its ecosystem token $OPAI. Therefore, voters staking $OPAI have an incentive to vote for the optimal AI Agent to maintain the price of their assets. Agents with poor performance receive reduced incentives, motivating builders to continuously optimize them to cover their training costs and earn rewards, while also receiving incentives from intent creators during the optimization process.
The ve model often performs well in balancing various game aspects. Furthermore, at the chain level, it can create enough second-layer product space for ecosystem developers. For example, developing a Convex-like product on top of the intent governance framework to unlock vlOPAI liquidity and delegate voting. The previous round of DeFi Governance War might appear in a different form within Optopia.
Optopia Overview: Summary and Future Prospects
In the design of Optopia, the introduction of AI Agents expands the intelligent execution paths at the chain level for Solver capabilities, while the adoption of the ve model perfectly addresses the incentive issue for Solvers. Since its mainnet release, Optopia is attracting more and more Agent builders to join, truly realizing its role as a user-friendly gateway for millions of users to enter Web3.
On June 13th, Optopia announced the completion of its seed round financing, with participation from G·Ventures, Kucoin Ventures, JRR Capital, KKP International Limited, ZenTrading, Klein Labs, MCS Capital, several cutting-edge venture capital firms, and blockchain notable individual investor MrBlock, providing Optopia with funding and strategic guidance. The raised funds will be used to accelerate the continuous upgrading and optimization of Optopia’s infrastructure, enhance AI capabilities, build decentralized technology, and increase community engagement.
As an ordinary user, Optopia also offers the opportunity to participate in this feast and acquire early chips. Optopia conducts initial token issuance through Gas Mining, where users can mine by consuming gas fees during specific Booster Events, thus receiving corresponding token rewards. This issuance can further enhance user participation in the network and achieve initial transaction activities and network growth, kickstarting the entire economic ecosystem.
AI, as one of the major narratives in this bull market, its organic integration with crypto is an exploration actively pursued by many practitioners. As a pioneer in the AI Agent field, Optopia’s practice of combining AI with intent also holds positive exploratory significance for the entire market.
