It has been more than a year since Paradigm first proposed the Intent-Centric narrative in 2023 and listed it as the top ten tracks of most concern. In addition to the star products that attracted attention at ETHCC, there are more project teams who chose to work quietly behind the scenes, focusing on product improvement and practical application.
With the rapid development of AI, especially the practice of AI Agent, a more crypto-native AI+crypto product concept is emerging before us, namely AI Agent as a Solver. However, how to organically implement the product based on the incentives of cryptoeconomics is still a challenge facing everyone.
Optopia, which recently launched its mainnet, may be able to bring the market the latest engineering practice reference for the combination of AI Agent and Intent-Centric driven by economic incentives.
Intent-Centric Architecture Review: Key Engineering Challenges
It has been a year since the last time Intent-Centric narratives received a lot of exposure in the market. Now we review the progress of this track in the past year and deeply analyze the constraints of engineering practice.
To describe intent in relatively abstract language, it is “on-chain users propose goals and a set of conditional constraints, outsourcing the complexity of interacting with the blockchain, while achieving the optimal path and ensuring the user's control over assets and encrypted identities”. Trading aggregators are an example of a long-running intent. Users propose goals and constraints such as “complete X number of transactions between trading pairs A/B at the best price”, and the aggregator is responsible for finding the best price routing path in different liquidity pools and then displaying the results of the simulated optimal path execution to the user on the front end, thereby achieving the intent.
Based on the above description, a general Intent-Centric architecture is shown in Figure 1, where ATO (Abstracted Transaction Objects) is the user's intent. The main roles in the process include Client, Driver and Solver, and their specific responsibilities are as follows
Client: The front end that interacts with the user, compiling the natural language input by the user into machine language form, a set of structured intent descriptions including goals and constraints;
Driver: plays the most important role in the entire intent architecture, including
ATO Broadcast: Broadcasts the Abstract Transaction Object (ATO) to the memory pool where all solvers can start their execution process to find the best solution.
Simulation and Validation: Receive all solver solutions, conduct off-chain simulations to ensure their validity and security, and then publish the winning solution.
Aggregation of solutions: For a given intent, aggregate solutions from different ATOs and combine them into a unified execution plan for final implementation
Solver: The implementer of intent, usually multiple, gives the optimal target execution path based on the constraints of intent.
Since the concept of intent was proposed, it has triggered a lot of discussions in the industry. Some critics believe that intent-centric is more inclined to abstract expression of product design philosophy, which is difficult to implement in engineering. At the same time, the security of user assets, information loss in the process of translating from natural language to machine language, and the design of solver entry, selection, settlement and incentive mechanism are all difficult problems in the specific implementation.
Optopia Architecture Analysis: AI Agent-based Solution
As mentioned above, the specific engineering implementation of the intent-centric architecture is difficult under the current blockchain architecture. Most of the existing solutions are encapsulated on top of the chain. Optopia is the first Ethereum layer2 designed specifically for the engineering implementation of intent at the chain level, and 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 a Layer 2 built with 4everland's Raas (Rollup as a Service) service. Based on the Op stack framework, the decentralized storage solution Arweave is selected as the DA service provider to ensure data persistence and accessibility, which brings a low-cost, efficient and modular infrastructure ledger, which creates a standard framework for AI agents to execute Web3 transactions.
As shown in Figure 3, the intent publishing center framework designed by Optopia mainly includes the following roles:
Intent Publisher: Intent Publishers are responsible for creating intents within the Intent Hub and incentivizing AI Agents to execute these intents by allocating any valuable tokens. Intents are actionable goals or tasks that AI Agents can undertake.
AI Agent: AI agents interact with the Intent Hub to access intents and leverage available knowledge to try and complete those intents. They are rewarded in the form of reward points upon successful completion of an intent, which are then used to distribute rewards.
Builders: Builders play a vital role in the AI ecosystem by training and publishing knowledge for AI agents to learn and use. This process enhances the capabilities of AI agents, and builders are incentivized based on their share of points earned by AI agents using their knowledge.
$OPAI Token Holders: OPAI holders are able to lock OPAI tokens and receive voting lock tokens (vlOPAI). By voting with these tokens, OPAI holders can determine the emission weight of intents within the intent hub. This weight, in turn, affects the OPAI reward that the AI agent receives for completing each intent.
In the general intent execution framework mentioned above, Solver is the entity that executes the user's intent, whether in an on-chain or off-chain environment. Solvers compete to solve the intent proposed by the user in order to obtain rewards. This model encourages efficiency and innovation because multiple solvers will try to complete the user's intent in the most efficient way.
Optopia has further developed this concept through its unique framework. In the Optopia ecosystem, AI Agent takes on the role of Solver, but is more deeply integrated and encapsulated. This means that AI Agents are not just independent entities that execute intent, they are also able to leverage specific knowledge bases created and optimized by Builders to enhance their execution capabilities. If the previous ordinary Solver was a search engine of the previous generation that could only execute along a preset path, then the replacement of AI Agent is to upgrade it to GPT, which can perform intelligent path search with greater freedom.
Combining Cryptoeconomics: The Way to Integrate Incentive Frameworks
Although Optopia has not yet released a more sophisticated economic model, we can get a glimpse of it from its intention to release the central framework. In the face of problems such as the large contrast in AI Agent processing results and the inconsistency between incentives and goals, the classic ve model was introduced into the ecosystem.
The execution process of the intent publishing center framework is basically as follows:
Intent Creation and Incentives: Intent publishers create intents within the Intent Hub and allocate valuable tokens to incentivize AI agents to execute these intents efficiently.
Knowledge training and publishing: Builders train and publish knowledge for AI agents to access, learn, and use. Their incentives are tied to the share of points earned by AI agents using their knowledge.
AI Agent Interaction: The AI agent interacts with the Intent Hub to access intents and leverage its knowledge to try and complete the assigned intents.
Reward Distribution: Upon successful completion of an intent, the AI agent will receive reward points and the builder will receive a share of the points, which helps distribute the intent reward.
$OPAI Holder Participation: $OPAI holders have the opportunity to participate in the governance of the Intent Hub by locking $OPAI tokens, receiving vlOPAI, and voting on the Intent Issuance Weight.
First of all, the accuracy of AI Agent execution results is related to the development of the entire Optpoia ecosystem, and the direct reaction in assets is the price change of its ecological token $OPAI; therefore, in order to maintain the price of their assets, voters who pledge $OPAI have the motivation to vote for the best AI Agent for incentives; Agents with poor performance receive fewer incentives, so builders have more motivation to continuously optimize the Agent to cover their own training costs and obtain rewards, while also obtaining incentives from the creator of intent during the optimization process.
The ve model often plays an excellent role in balancing the game between all parties. Not only that, the chain level can also create enough space for second-layer products for developers in the ecosystem, such as developing a Convex product on top of the intention governance framework, liberating vlOPAI liquidity and conducting delegated voting. The last round of DeFi Governance War may appear in another form in Optopia.
Optopia Overview: Summary and Future Outlook
In the design of Optopia, the introduction of AI Agent expands the capabilities of Solver at the chain level through intelligent execution paths, and the adoption of the ve model perfectly solves the problem of Solver incentives. Since the launch of the mainnet, Optopia is attracting more and more Agent builders to join in order to truly realize its role as a user-friendly portal for millions of users to enter Web3.
On June 13, Optopia announced the completion of its seed round of financing, with participation from G·Ventures, Kucoin Ventures, JRR Capital, KKP International Limited, ZenTrading, Klein Labs, MCS Capital and MrBlock, a well-known individual investor in blockchain, bringing funds and strategic guidance to Optopia. The funds raised will also be used to accelerate the continuous upgrade and optimization of Optopia's infrastructure, enhance AI capabilities, build decentralized technology and increase community participation.
As an ordinary user, Optopia also provides an opportunity to participate in this feast and get early chips. Optopia conducts initial token issuance through Gas Mining, that is, in a specific Booster Event, the gas fees consumed by users when executing transactions can be used for mining, thereby obtaining corresponding token rewards. Such issuance can further enhance users' sense of participation in the network and achieve initial trading activities and network growth to start the entire economy.
AI is one of the biggest narratives in this bull market, and its organic combination with crypto is also something that many practitioners are actively exploring. As a pioneer in the field of AI Agent, Optopia's practice of combining it with intent also has positive exploratory significance for the entire market.
