The digital frontier is constantly expanding, and at its vanguard, Artificial Intelligence (AI) Large Models and the Metaverse are converging to forge a new paradigm of economic activity. This is no longer the realm of science fiction; it is the strategic imperative driving innovation in 2025. DBiM, short for “Doing Business in Metaverse,” stands at the forefront of this evolution, dedicated to exploring, building, and empowering commercial activities within this rapidly evolving digital realm. Our mission is to leverage cutting-edge AI Agent technology and innovative platform operations to construct an efficient, intelligent, and autonomously collaborative metaverse economic service platform. At the heart of this grand vision lies the Autonomous Agent-Driven Metaverse Economy (AADME), a sophisticated ecosystem where highly autonomous AI Agents are the primary participants and driving force behind economic activity, value creation, and resource allocation. This article delves into the intricate architecture and profound implications of AI Agents as the intelligent backbone enabling DBiM’s pioneering AADME.

The Fragmented Digital Landscape: A Call for Intelligent Navigation

The modern digital experience, while rich in content and services, is increasingly plagued by fragmentation and friction. Consumers today navigate a bewildering maze of dozens of websites and applications, suffering from information overload and “subscription fatigue.” The arduous task of planning complex activities, such as travel, often involves hours of research across numerous disparate platforms, leading to a “fragmented planning and booking” experience. This pervasive pain point creates an immense market opportunity for aggregators capable of unifying and simplifying these disparate digital experiences.

DBiM’s strategic approach stands in stark contrast to the paths taken by many early metaverse entrants. We explicitly avoid the “idealized” and ultimately flawed strategy of building a grand but empty virtual world first. Unlike Meta’s immersion-first approach, our technology does not demand users enter a separate virtual reality; instead, it seamlessly integrates into and enhances their existing digital lives, augmenting rather than replacing their current application scenarios. Furthermore, our model diverges from the closed economic platforms of gaming giants like Roblox or Fortnite. While these platforms boast successful internal economies, their proprietary virtual currencies are non-transferable and lack the price stability tied to the real world. DBiM’s stablecoin economy is designed from its inception to be open and interoperable, fostering a more transparent and equitable system for all participants. Moreover, unlike traditional “super apps” such as WeChat or Grab, which solve fragmentation by building walled gardens of bundled services, DBiM’s AI Agent acts as a sophisticated navigator across the open internet, offering a more flexible and less restrictive aggregation model.

Our core premise is clear: the most effective pathway to building the next-generation internet is not to replace the existing web, but to construct an intelligent layer atop it. By addressing the usability challenges of today, DBiM is strategically positioned to build the user base, trust, and infrastructure essential for the spatial internet of tomorrow. This pioneering business model seamlessly fuses the essence of Web 2.0 aggregation platforms with Web3 architecture and spatial computing user interfaces, creating a novel hybrid aggregation paradigm. Its foundational function—navigating and simplifying access to existing Web 2.0 applications—is characteristic of an aggregator platform, designed purely for user convenience. However, unlike traditional aggregators that build centralized platforms, DBiM introduces a stablecoin for asset exchange in its second phase, a hallmark of Web3 ecosystems prioritizing interoperability and transparent value transfer. Concurrently, its user interface, envisioned as a “virtual reality navigator,” represents a spatial computing interface, a profound departure from the 2D mobile interfaces of conventional super apps. By combining these three elements, DBiM not only delivers the immediate utility of a Web 2.0 aggregator but also possesses a future-proof economic and UI architecture, effectively bridging the current internet with the spatial internet of the future, establishing a distinct competitive advantage.

AI Agent: The Intelligent Compass of the Metaverse

At the core of DBiM’s first stage, “Intelligent Navigation,” is the deployment of an AI-driven intelligent agent. This is not merely an algorithm but a sophisticated “life partner” for the user, designed to simplify and automate a wide array of tasks across existing Web 2.0 application ecosystems. Technically, this “AI assistant” aligns with a precise concept: the Large Action Model (LAM), often referred to as Agentic AI. Unlike Large Language Models (LLMs) that primarily process and generate text, LAMs are specifically engineered to execute actions and accomplish complex, multi-step tasks within digital environments. This represents the pivotal technological innovation of our initial phase.

The intelligence of our AI Agent is rooted in a Vision-Language-Action (VLA) architecture, empowering it to comprehend natural language requests from users—for instance, “Find me a small wooden desk suitable for a home office”—and then execute that request on third-party websites like Taobao. The Vision component leverages advanced computer vision technology to parse the user interface of any application, identifying elements such as buttons, text fields, and images, critically without needing access to their underlying code or APIs. This ensures universal compatibility. The Language component, powered by its LLM core, interprets user intent, meticulously breaking down requests into a sequence of actionable steps. For example, it can deduce: “1. Open the Taobao app; 2. Enter ‘wooden desk’ into the search box; 3. Filter for ‘small size’; 4. Add the top three results to the shopping cart.” It also engages in sophisticated reasoning about information displayed on the screen. Finally, the Action component programmatically executes these steps by simulating clicks and keyboard inputs, effectively automating the user’s workflow. The successful application of this technology by companies like Adept AI in enterprise workflows validates its immense viability.

What truly elevates this AI Agent from a simple automation tool to a genuine personalized assistant is its remarkable ability to learn and record user preferences, historical interactions, and individual characteristics. This profound capability allows it to perform “pre-priming and pre-management”—for instance, pre-filtering products based on known style preferences and budget constraints. This transformative capacity ensures that the AI Agent becomes not just a helpful utility but an indispensable daily application, deeply integrated into the user’s digital life.

The AI Agent is not merely a product feature; it is a potent, self-sustaining user acquisition engine. The greatest hurdles for any new platform are user acquisition and overcoming existing user inertia. People are naturally reluctant to alter established habits. DBiM’s AI Agent directly targets the most friction-laden pain points in digital life: from the necessity to browse dozens of websites and spend hours researching travel plans to the complexity of managing myriad subscription services. By automating these cumbersome tasks, the AI Agent delivers immediate and immense value, transitioning from a “nice-to-have” tool to an “indispensable” everyday companion. This profound utility serves as a powerful “hook” for initial user adoption. Once users begin to rely on the AI Agent for complex tasks, their switching costs become exceptionally high, as the agent has seamlessly learned all their preferences and deeply integrated into their workflows. Therefore, the practical utility of the AI Agent is the core driver attracting users into the DBiM ecosystem, and this burgeoning user base forms the bedrock for the network effects that will propel subsequent stages, including our economic layer and curated cultural experiences. The AI Agent is truly the engine powering the entire business model’s flywheel.

The DBiM Metaverse AI OS: Orchestrating Autonomous Collaboration

To support and manage a vast network of AI Agents and their intricate interactions, DBiM is building a Platform-as-a-Service (PaaS) level “DBiM Metaverse AI OS.” This operating system is the intelligent central nervous system and technical foundation of our entire ecosystem. It provides standardized development tools, API interfaces, modular AI algorithms, data processing and analysis capabilities, and core metaverse infrastructure services, all meticulously designed to ensure platform openness, scalability, and highly efficient collaboration.

The core functions and PaaS characteristics of our OS include:

• Standardized API & SDK: Offering a rich suite of API interfaces and software development kits, significantly lowering the barrier for developing AI Agent applications and metaverse scenarios.

• Modular AI Capabilities: Integrating core AI Agent capabilities such as natural language processing, computer vision, reinforcement learning, knowledge graphs, and emotional computing, available for various business units to invoke on demand.

• Data Management & Analysis: Providing unified data access, storage, processing, and analysis services, supporting AI model training and robust business intelligence decision-making. This includes building a personalized digital consumption database, allowing AI Agents to analyze behavior across gaming, shopping, and social contexts to create dynamic, multidimensional user profiles.

• Metaverse Infrastructure Services: Encompassing distributed identity authentication, virtual asset management interfaces (with blockchain integration), scene rendering and physics engine support, and cross-platform communication protocols.

• Scalability & High Availability: Employing cloud-native architectures like microservices and containerization to ensure dynamic scaling for high concurrency demands and stable, reliable service.

• Security & Compliance: Embedding a robust security protection system and privacy mechanisms to safeguard data and meet regulatory requirements.

This OS acts as a powerful enabler, both internally and for the future ecosystem. Internally, it accelerates the integration and synergy among various business modules, boosting development efficiency, reducing operational costs, and enabling rapid iteration and service innovation. For the broader ecosystem, the OS will gradually open to third-party developers and enterprises, empowering them to build and deploy their own AI Agent applications and services on our platform. This openness will dramatically enrich the content and service diversity within the DBiM metaverse ecosystem, fostering powerful network effects. Monetization strategies for the OS include subscription models for enterprises and advanced developers, usage-based fees for API calls and AI model resources, charges for value-added modules, and future marketplace revenue sharing from third-party applications.

AADME: Where AI Agents Drive Economic Symphony

The “Autonomous Agent-Driven Metaverse Economy” (AADME) is the ultimate realization of DBiM’s vision, brought to life through the synergistic power of AI Agents orchestrated by the DBiM Metaverse AI OS. The core principle here is the “autonomous collaborative economic service effect.” This refers to the ability of disparate AI Agents—whether those representing different business modules or those acting on behalf of individual users—to transcend simple information exchange. Instead, they autonomously perceive, intelligently decide, dynamically negotiate, and collaboratively act based on shared goals or complementary needs. This organic, interconnected behavior leads to an emergent, macro-level value enhancement and innovation where the whole is greater than the sum of its parts.

In this intricate dance of digital commerce, the AI Agent assumes three critical roles:

• Connector: AI Agents possess the unique ability to comprehend the semantics and requirements of diverse business scenarios, proactively discovering and establishing cross-scenario, cross-business connections, effectively dismantling information silos.

• Optimizer: Through continuous learning and real-time data analysis, AI Agents relentlessly optimize existing processes, resource allocation, and user experiences, ensuring peak efficiency and satisfaction.

• Innovator: By recognizing complex patterns within vast datasets and intricate interactions, and by intelligently combining different capabilities, AI Agents can assist in, or even autonomously generate, entirely novel service models and solutions.

The synergistic effects within AADME manifest in several profound ways:

Cross-Module Service Integration and New Value Creation

Imagine a user’s gaming AI Agent in the virtual item trading market discovering a high-value item, but the user’s funds are insufficient. This AI Agent can autonomously invoke its personal financial AI Agent to assess the user’s financial standing and apply for a small “virtual asset mortgage loan” or “installment payment” service. Upon successful transaction, the user’s social AI Agent might, based on pre-set preferences, share this achievement—perhaps showcasing a rare piece of equipment—within fan communities or gaming groups, potentially triggering purchasing or financial service demands from other users.

Consider another scenario: an enterprise’s B2B trade AI Agent completes a cross-border procurement. The data from this transaction can be seamlessly transmitted through the OS to the e-commerce supply chain AI Agent, which then optimizes inventory and replenishment plans. Concurrently, the trade credentials and logistics information are routed to the financial service AI Agent, automatically triggering supply chain finance services such as accounts receivable financing or order financing. This exemplifies how AI Agents facilitate complex, multi-stage commercial processes with unprecedented fluidity.

Data-Driven Hyper-Personalization and Precise Services

User behavior data—encompassing preferences and activities across gaming, shopping, and social platforms—can be integrated and analyzed at the DBiM Metaverse AI OS level, always under user authorization and stringent privacy protection. This holistic analysis yields a user profile far more precise, dynamic, and multi-dimensional than any single-platform data could provide. Based on this rich, integrated understanding, the platform can deliver truly “thousand-person-thousand-face” hyper-personalized service recommendations, content presentations, and interactive experiences. For example, a user deeply passionate about a specific type of in-game equipment might have their e-commerce AI Agent prioritize recommendations for physical merchandise related to that game’s IP or virtual fashion items with similar aesthetics. This is where the AI Agent’s role in intelligent navigation and recommendations becomes paramount, guiding users through the vast metaverse with unparalleled precision.

Exponential Improvement in Operational Efficiency and Cost Optimization

AI Agents are capable of automating a vast array of repetitive and rule-based tasks, including customer inquiries, order processing, content moderation, risk monitoring, and market data collection. This drastically reduces human labor costs. Furthermore, the DBiM Metaverse AI OS, through its AI Agents, can monitor and predict the platform’s resource demands—such as computing power, storage, and bandwidth—in real-time. This enables dynamic optimization and allocation, significantly enhancing resource utilization and lowering operational expenses. Within the financial sector, AI Agents collaborate on fraud detection, credit assessment, and identification of market manipulation, bolstering the overall security of the ecosystem.

Network Effects and Positive Feedback Loops

The AADME fosters powerful network effects. The more users (and their AI Agents) participate, the richer the platform’s data becomes, leading to increasingly intelligent AI Agents and superior service experiences, which in turn attracts even more users. Similarly, as more business modules and service scenarios are integrated onto the platform and synergized by AI Agents, the combined value proposition of the platform expands exponentially, making it even more attractive to diverse user segments. In the future, as the OS opens to third-party developers, a thriving developer ecosystem will further amplify these user and service network effects.

The DBiM Metaverse AI OS ensures and promotes this pervasive synergy through several mechanisms: unified standards and protocols for AI Agent communication, data formats, and API interfaces; a capability registration and discovery mechanism allowing agents to find and invoke necessary services; a robust incentive and governance framework to encourage positive collaboration and prevent malicious behavior; and a secure data and knowledge sharing platform enabling AI Agents to learn and evolve from the entire ecosystem’s collective experience.

Building the Future: The DBiM Flywheel

DBiM’s business model is best characterized as an aggregator platform. We create value not by producing all services ourselves, but by organizing and simplifying access to a vast and fragmented existing digital service ecosystem. Strategic mergers and acquisitions are a critical component of this strategy, allowing us to quickly integrate “standardized, general-purpose” applications targeting specific demographics—such as fan communities or game item trading platforms—to rapidly kickstart ecosystem growth by acquiring existing network effects.

Our strategy can be clearly mapped to Jim Collins’s “Flywheel Effect,” where a series of well-executed steps generates compounding momentum, ultimately becoming virtually unstoppable. The DBiM flywheel effect can be broken down into the following virtuous cycle:

1. Providing Exceptional Utility: Our AI Agent, in its intelligent navigation phase, addresses core user friction points, delivering immense value and attracting an initial user base.

2. Enhancing User Engagement: As more users depend on the AI Agent for daily tasks, the platform collects anonymized data on user needs and behaviors, providing a rich dataset for continuous AI improvement and the discovery of new opportunities.

3. Attracting Third-Party Partners: A growing and highly engaged user base becomes a valuable audience, drawing in third-party service providers and brands eager to integrate with the DBiM ecosystem. Strategic acquisition of “built-in” applications further accelerates this process.

4. Establishing Economic Lock-in: The DBiM stablecoin, in its second phase, emerges as the default, low-friction method of transaction within this expanding ecosystem, creating economic stickiness for both users and partners.

5. Boosting Network Effects: With an increasing number of users, partners, and economic liquidity, the platform’s overall value proposition grows exponentially. This robust network effect makes it challenging for competitors to challenge us and makes it easier for DBiM to attract the next wave of users.

6. Driving Further Innovation: The revenue and data generated by the flywheel are reinvested into improving the core AI Agent and developing new, curated experiences, which in turn provide even more utility, causing the flywheel to spin faster. This is the very model by which technological ecosystems are built and sustained.

Conclusion and Future Trajectory

DBiM’s commercial model, driven by AI Agents and underpinned by the DBiM Metaverse AI OS, strategically integrates diverse business scenarios to construct an unprecedented “autonomous collaborative economic service platform.” The success of this model transcends DBiM’s own achievements; it has the potential to pave new pathways for the commercialization of the entire metaverse industry and the deeper application of AI technology. Its core value lies in leveraging AI-driven synergy to dismantle traditional business boundaries, unlock the full potential of data and intelligence, and generate exponential economic value and unparalleled user experience enhancements. This journey, while undoubtedly challenging, holds the immense opportunity to define the future of digital commerce. DBiM is committed to continuous technological leadership, aiming to evolve the DBiM Metaverse AI OS into a leading open platform that attracts global developers. Our vision extends to exploring cutting-edge applications like digital twin cities and industrial metaverses, with the ultimate goal of becoming a core engine and standard-setter for global metaverse economic development, ensuring that everyone benefits from the intelligent metaverse era.