Multi-Agent Collaboration in the Field of Decentralized Finance: A Case Study of Theoriq

Starting from 2024, AI Agents will rapidly rise in the Web3 world, with a large number of experiments surrounding agents emerging. As an intermediary bridge between model capabilities and specific business applications, AI Agents will encapsulate underlying AI models into agents with task-oriented and autonomous capabilities, directly serving users to independently execute tasks and generate real economic activities.

1. AI Agent Protocol Stack Levels

In the entire AI Agent protocol stack, it 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.

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

3. Application Layer: Covers subcategories such as distribution, application, and consumption, including Agent Launchpad, AgentFi, Agent Native DApp, etc.

2. AgentFi: A Practical and Verifiable Direction for Implementation

AgentFi may be the most promising evolutionary direction at the current stage to achieve a balance between "engineering feasibility + business viability". It mainly focuses on the following sectors:

1. Lending: Automated interest spread arbitrage and cross-protocol capital allocation.
2. Trading Category: Focus more on "intent-based automated execution".
3. Liquidity Mining/LP Management: Focused on automated execution of centralized LP strategies, intelligent rebalancing under volatility awareness, etc.

3. Theoriq: The Evolution of Liquidity Management for Agent Swarm

Theoriq aims to create an agent economy through the coordination of AI agent clusters, with on-chain liquidity management and yield optimization being one of its important application scenarios.

Theoriq Alpha Protocol

Theoriq Alpha Protocol is a decentralized protocol designed to support multi-agent collaboration on-chain, execute complex financial tasks, and optimize liquidity. Its core features include:

• Messaging and Coordination Mechanism
• Agent Public Registration System
• Configurable Agent Template
• Developer Integration Tools
• AlphaStudio User Terminal

Theoriq AlphaSwarm

AlphaSwarm is the first flagship multi-agent system built on Theoriq Alpha Protocol, composed of three types of core agents:

• AlphaSwarm Portal Agent
• AlphaSwarm Knowledge Agent
• AlphaSwarm LP Assistant Agent

Four, Theoriq Ecosystem Cooperation and Community Development

Theoriq is building a multidimensional ecological network that encompasses AI infrastructure, data collaboration, computing power acceleration, and community co-construction. Major partners include Google Cloud, NVIDIA, Kaito, Arrakis Finance, Keyrock, and others.

At the community level, Theoriq has launched the "Infinity Swarm" global ambassador program, establishing multiple tiers for content creators and community builders.

5. Token Economic Model Design and Governance Security Mechanism

Theoriq's token $THQ is positioned as the core "fuel" of the decentralized agent network. The total supply is fixed at 1 billion, and the token distribution structure includes core contributors, investment institutions, community incentives, and the treasury.

$THQ holders participate in the network to obtain diversified incentive methods, including protocol access fees, direct incentives and ecological rewards, agent incentives, and delegation mechanisms.

6. Project Financing and Team Background

The development team behind Theoriq, ChainML, has completed two rounds of financing, raising a total of $10.2 million. The core team members come from tech and financial giants such as Google, ConsenSys, Goldman Sachs, and Dell.

7. The Competitive Landscape of the Agent Market

There are not many competitors in the niche direction of AgentFi + Decentralized Finance liquidity management for Theoriq. Compared to projects like Olas, Talus, and Virtual Protocol, Theoriq focuses more on building a financial intelligent Agent network that can generate profit.

8. Conclusion: 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 from concept to practicality. The project has a solid foundation of real-world demand and a clear commercial application path, while also introducing LLM, reinforcement learning, and on-chain real-time signal processing in its engineering implementation, pushing the agent system towards strategic and adaptive evolution.