The Rise of AI Agents in Web3 and Future Development

Since 2024, AI Agents have rapidly developed in the Web3 field, with numerous experiments surrounding agents emerging. From a holistic AI perspective, AI Agents not only play the role of interaction and execution layers, but also represent a user-oriented intelligent product form. They bridge the gap between model capabilities and specific business applications, encapsulating underlying AI models into intelligent agents with task-oriented and autonomous capabilities, directly serving users to autonomously execute tasks and generate real economic activities.

AI Agent Protocol Stack Levels

The AI Agent protocol stack can be divided into three main layers:

1. Infrastructure Layer: Provides the lowest level of operational support for agents, including core modules such as Agent Framework and Agent OS, as well as supporting modules like Agent DID and Agent Wallet.

2. Coordination and Scheduling Layer: Focus on the collaboration among multiple agents, task scheduling, and system incentive mechanisms, including Agent Orchestration, Agent Swarm, and Agent Incentive Layer.

3. Application Layer: includes distribution subclasses ( such as Agent Launchpad ), application subclasses ( such as AgentFi ), consumption subclasses ( such as Agent Social ), etc.

AgentFi: Practical Feasibility and Value-Proven Implementation Direction

AgentFi is currently the most promising evolutionary direction for achieving a balance between engineering feasibility and business usability. The main areas of focus include:

1. Lending: Automated interest rate arbitrage and cross-protocol capital allocation

2. Transaction type: More focused on intention-based automated execution

3. Liquidity Mining/LP Management: Focus on Automated Execution of Centralized LP Strategies

Among them, LP management is one of the areas with the highest technical barriers, requiring real-time responses to price fluctuations, changes in volatility, and the accumulation of transaction fees.

Theoriq: The Evolution of Liquidity Management for Agent Swarm

Theoriq aims to achieve an agent economy by coordinating a cluster of AI agents, and its flagship product Alphaswarm has chosen liquidity management as its entry point. The Theoriq Alpha Protocol is a communication and execution protocol stack designed for Agent collaboration, featuring messaging and coordination mechanisms, a public registration system for Agents, and configurable Agent templates.

AlphaSwarm is the first flagship multi-agent system built on Theoriq Alpha Protocol, consisting of three core agents: Portal Agent, Knowledge Agent, and LP Assistant Agent, forming a complete closed-loop process of task discovery - data analysis - strategy generation - on-chain execution.

Theoriq Ecosystem Cooperation and Community Development

Theoriq is building a multi-dimensional ecological network covering AI infrastructure, data collaboration, computing power acceleration, and community co-construction, in cooperation with Google Cloud, NVIDIA, and others. At the community level, the "Infinity Swarm" global ambassador program has been launched, and active participation in global core cryptocurrency conferences is taking place.

Token Economic Model Design and Governance Security Mechanism

Theoriq has released the design of its token economic model, clearly positioning $THQ as the core "fuel" of the agent network. The total supply of $THQ is fixed at 1 billion tokens, allocated to core contributors, investment institutions, community incentives, and the treasury. Holders can participate in the network and earn rewards through staking, locking, and delegation.

Project Financing and Team Background

The development team behind Theoriq, ChainML, has completed two rounds of financing, consisting of AI experts and blockchain engineers from tech and financial giants such as Google and ConsenSys.

Competitive Landscape of the Agent Market

Unlike general-purpose Agent networks like Olas and Talus, Theoriq clearly focuses on on-chain application scenarios that are capital-intensive and have frequent interactions in the DeFi space. In the niche direction of AgentFi + DeFi liquidity management, there are not many competitors in the track where Theoriq Alpahswarm is located.

Summary: Business Logic, Engineering Implementation and Potential Risks

Theoriq focuses on the core pain points of DeFi—liquidity management and automated asset operation, representing the key path for AgentFi to transition from concept to practicality. Its engineering implementation is challenging but feasible and worthwhile, with solid underlying capabilities, clear scenario compatibility, and a strong adaptive foundation in the DeFi market, holding the potential to become a long-term infrastructure target for AgentFi.