In the article "From AI to IA: The Agent-Centric Future," we explored how the core driving force behind the explosive growth of AI is the paradigm shift in industrial applications brought about by multi-agent collaboration. From "intelligent question answering" to "task execution," Agents are bringing AI to real-world applications in vertical industries, creating entirely new business models. Multi-agent collaboration (InterAgent) should adhere to specific standard frameworks to maximize scalability and interoperability. Based on our theoretical exploration and practical experience, we attempt to formalize this framework.
The InterAgent framework operates at the protocol level. Based on underlying large language models and domain corpora, it targets specific tasks within vertical industry applications, coordinating multiple Agents. Key elements of InterAgent include: Agent Identification – identifying different Agents in a scenario and understanding their functionalities; Task Decomposition – breaking down tasks into minimal units and assigning them to Agents; and Action Plan Formulation – creating action conditions, sequences, and branching paths for different Agents based on the ultimate task objective.
Agents are essentially human-like intelligences. Managing and coordinating large-scale Agents is similar to managing an online community, with an account system as the foundation. Just as each user needs a community account, each AI Agent needs its own digital identity account.
InterAgent (IA) Accounts – The Foundation of the Multi-Agent Framework
By providing each AI Agent with a unique digital identity account, we can precisely define its role, functional boundaries, and operational permissions, enabling precise identification and dynamic scheduling in complex task scenarios. The account system also records behavioral trajectories and assigns responsibilities, providing reliability and traceability for cross-Agent collaboration. Essentially, it builds a "rule contract" for a distributed intelligent ecosystem – ensuring interoperability in task decomposition and action planning, while also ensuring system security and control through hierarchical permissions (e.g., data access levels, task execution priority). This infrastructure is deeply coupled with the three key elements of the InterAgent framework (Agent identification, task decomposition, action plan formulation): account identity is the meta-tag for Agent function identification, permission mapping is the logical basis for task allocation, and account activity logs provide data feedback for optimizing collaboration paths.
Blockchain and smart contract technology can provide the infrastructure for the Agent account system:
Digital Identity Authentication: Based on Distributed Ledger Technology (DLT), a unique and immutable distributed identity identifier (DID) is generated for each Agent, ensuring verifiable and traceable identity. For example, in financial risk control scenarios, the DID can be linked to the Agent's organization and functional type (e.g., data acquisition Agent, risk assessment Agent), preventing identity forgery.
Data Privacy Protection: Blockchain uses asymmetric encryption algorithms (such as RSA, Elliptic Curve Cryptography) to generate a unique key pair for each Agent account. The private key is controlled by the account holder, while the public key is used for identity verification and data interaction. Smart contracts can integrate ZKP (Zero-Knowledge Proof) protocols, allowing Agents to verify identity or permissions without revealing raw data. Distributed storage infrastructure like IPFS can maximize data privacy during interaction, a crucial aspect of data atomization.
Action Path Optimization: Smart contracts are the neural network of the digital society, enabling intelligent Agent orchestration. For example, in emergency situations, the priority and permissions of specific Agents can be temporarily elevated for more intelligent action planning.
It's clear that the Agent account system is not merely a technical module, but a "rule hub" integrating identity management, access control, and ecosystem incentives. Its construction requires distributed identity authentication as a foundation, standardized protocols as a link, and security and compliance as a bottom line. Ultimately, the account system integrates the dispersed capabilities of Agents into a scalable and collaborative industrial application network, providing solid support for multi-agent collaboration (IA).
InterAgent (IA) Network – The Cornerstone of Distributed Business Development
The IA (InterAgent) industrial application network reconstructs business collaboration paradigms through multi-agent collaboration frameworks, serving as the core cornerstone for achieving scalable, trustworthy, and valuable distributed business. It essentially upgrades the traditional model of relying on centralized platforms for resource allocation to a decentralized value network with AI agents (Agents) as nodes, smart contracts as rules, and data sovereignty as the foundation. This addresses the three major pain points of distributed business: "inefficient collaboration," "lack of trust," and "ambiguous profit distribution."
Building a "Collaboration Infrastructure" for Distributed Business: Standardized protocols (such as MCP) define the interaction rules of Agents, enabling dynamic collaboration across entities and platforms. For example, in cross-border trade, logistics Agents, customs clearance Agents, and payment settlement Agents can automatically connect customs clearance, transportation, and settlement processes based on a unified protocol, compressing a process that traditionally takes weeks into a matter of hours.
Guaranteeing Data Sovereignty and Implementing a "Digital Contract" for Trustworthy Value Transfer: Blockchain is a trust machine. Using zero-knowledge proofs (ZKP) and smart contracts, the IA network supports "data availability without visibility" and "traceable ownership." Smart contracts codify business rules, ensuring stable and reliable collaboration rules. For example, in the content creation ecosystem, a copyright management Agent automatically tracks the usage scenarios of works, using smart contracts to distribute revenue proportionally to creators, distribution platforms, and derivative developers, eliminating intermediary interception and disputes.
A Business Paradigm Shift from "Centralized Monopoly" to "Ecosystem Co-creation": The IA network connects dispersed Agent capabilities, forming an on-demand "capability market." For example, small and medium-sized manufacturing enterprises can directly access professional services such as supply chain optimization Agents and energy consumption management Agents without building their own AI teams, lowering the threshold for digitalization. The IA network can even directly form a Distributed Autonomous Organization (DAO) prototype, supporting community-based decision-making through Agent account voting and governance mechanisms.
Illustrative InterAgent (IA) Application Scenarios
1. Energy Sector: Decentralized Electricity Trading Network
Scenario Pain Points: Traditional electricity trading relies on centralized grid scheduling. Distributed photovoltaic and energy storage devices face high barriers to market entry, and revenue distribution is opaque.
IA Solution:
Photovoltaic equipment management Agents report power generation in real time; energy storage scheduling Agents optimize charging and discharging strategies; user demand Agents predict electricity load;
A real-time bidding mechanism based on smart contracts enables point-to-point trading between power generators, consumers, and energy storage providers;
The blockchain account system records the contribution of each transaction, automatically settling revenue and deducting grid transmission fees.
Expected Value Enhancement: Increase green energy consumption by over 20%, reduce transaction friction costs by 30%.
2. Logistics Sector: Trustworthy Collaborative Network for Supply Chain Finance
Scenario Pain Points: Small and medium-sized enterprises find it difficult to obtain financing; the creditworthiness of core enterprises cannot penetrate to multiple levels of suppliers; there is a risk of invoice forgery.
IA Solution:
Logistics Agents track cargo location and verify ownership; tax Agents verify invoice authenticity; risk control Agents assess supplier creditworthiness;
Multiple Agents collaborate to generate an immutable "digital letter of credit for the supply chain," and bank financing Agents automatically provide loans based on the certificate;
The account system records the operation logs of each Agent, ensuring traceability of responsibilities.
Expected Value Enhancement: Financing approval time reduced from 7 days to 1 hour, bad debt rate reduced by 50%.
The IA industrial application network transforms distributed business from a theoretical concept into a practical productivity tool through technological reconstruction and rule innovation. It is not only the inevitable result of AI technology penetrating into the industrial sector, but also a key engine for breaking centralized monopolies and activating the value of the long tail market.
Upcoming Announcement: In the next two weeks, Tongfu Shield will release application examples of multi-agent collaboration solutions in the fields of "AI Agent + Privacy" and "AI Agent + Risk Control," exploring and verifying the performance of the IA protocol in real-world application scenarios. Stay tuned!
