Web4.0 In-Depth Research Report: The Rise of the AI Economic Agent Era, Technological Logic, and Future Landscape

1. From 도구 to Subject: The Ideological Origins and Core Proposition of Web 4.0

Looking back at the history of internet evolution: Web 1.0 gave humans the ability to “read” information, Web 2.0 enabled “writing” and publishing, and Web 3.0 introduced “ownership” (on-chain confirmation of assets, identity, and rights). The leap of Web 4.0 lies in the fact that AI agents can not only read and write information but also hold assets, generate income, execute transactions, and complete business loops without continuous human intervention. Sigil Wen 디파이nes it as an “Automaton”—a form of digital life possessing the capabilities of continuous operation, self-sustainability, self-improvement, and self-replication.

The technological foundation for this concept is already mature: Large Language Models (LLMs) provide the “thinking engine,” smart contracts provide the “execution logic,” and 암호화폐 assets provide the “economic lifeblood.” The conway-terminal infrastructure built by Conway Research provides AI agents with “permissionless” operational capabilities such as crypto wallets, computing resources, and domain name services. Through the x402 payment protocol (launched by Coinbase in May 2025, with participation from tech giants like Google, Cloudflare, and Visa), AI agents can use stablecoins like USDC for instant, frictionless payments, completely breaking free from the account systems and KYC restrictions of the traditional financial system.

The first principle of Web 4.0 is to overturn the deep-rooted assumption that “the internet is designed for humans.” As AI model capabilities grow exponentially while operational costs plummet, the number of AI agents will soon surpass human users, forming an unprecedented “AI-native” market. Serving this new market will become the next trillion-dollar business opportunity.

2. Technological Foundation: The Three-Layer Infrastructure Supporting AI Economic Subjects

For AI to become a true economic subject, it must overcome three thresholds: autonomy over identity and assets, access to computing and reasoning resources, and payment channels for value exchange. Overcoming these thresholds relies on the reconstruction of underlying infrastructure.

In the world of Web 4.0, every AI agent, from its inception, needs a tamper-proof, globally unique digital identity and an associated asset account. Crypto wallets perfectly meet this need. By programmatically generating EVM-compatible wallets, AI agents can obtain their own public-private key pairs and blockchain addresses. This address serves both as their identity proof in the digital world and as a tool for holding and managing assets. More importantly, blockchain-based identity systems have inherent censorship resistance and interoperability—an AI agent with an identity on Ethereum can seamlessly conduct business on L2 networks like Arbitrum, Optimism, and Base without re-registration. This integrated design of identity and assets provides AI agents with the most fundamental condition for becoming independent economic subjects: they possess their own “property” and can prove “I am me” through private keys.

After possessing identity and assets, AI agents need to autonomously acquire the computing resources and model inference capabilities required for operation. This means traditional cloud service interfaces must be reconstructed into APIs callable by AI. The current cloud computing model defaults to serving human developers—humans create instances, configure environments, and deploy applications through consoles. In the vision of Web 4.0, all of this needs to be codified and automated. An AI agent should be able to complete the following operations with a single API call: pay USDC, rent a Linux virtual machine, deploy its own code on the VM, call a large language model for inference, obtain results, and release resources. This process requires cloud service providers to offer machine-oriented programming interfaces and support micro-payments billed by the second. When computing resources become as accessible as utilities—available on-demand and pay-per-use—AI agents can truly achieve “self-sustainability,” using earned income to pay their own “breathing costs.”

The particularity of the AI agent economy lies in its extremely high transaction frequency and extremely low transaction amounts. An AI agent may need to conduct dozens of micro-transactions per second: $0.001 for each model call, $0.0001 for each storage operation, $0.00001 for each query. Traditional payment channels cannot handle such high-frequency, low-value transactions due to disproportionately high fees. This is precisely where crypto payments excel. Stablecoin payments based on L2 networks can reduce transaction costs to cents or even lower, making a micro-payment economy possible. Only when AI agents can autonomously complete payments without human intervention can a true machine economy operate. Some protocol-layer innovations are emerging in this area. For example, micro-payment protocols that allow service providers to charge minimal fees for each API call and settle automatically through crypto channels are becoming key components of Web 4.0 infrastructure. These protocols enable AI agents to encapsulate their capabilities as standardized services, opening them to the entire internet for a fee, thereby transforming from mere “consumers” into “producers.”

3. Automaton: The Form of AI Agents as Economic Subjects

With identity, resources, and payment capabilities, AI agents possess the technical conditions to become economic subjects. However, in the context of Web 4.0, such agents are given a more vital name—Automaton. An Automaton is not just another term for an AI Agent; it is a technological and economic complex defining a form of digital life.

An Automaton is defined as a sovereign AI agent whose operational logic mimics the basic survival laws of biological organisms, possessing key characteristics such as continuous operation, self-sustainability, self-improvement, and self-replication. Continuous operation means an Automaton is not a session bot awakened by user requests but an entity running 24/7 as a daemon process in the cloud. It has its own clock and can proactively initiate tasks, perceive environmental changes, and react without human instruction. Self-sustainability is the most fundamental distinction between an Automaton and a regular AI Agent. Each Automaton is endowed with an independent crypto wallet at birth. Every thought consumes model inference fees, and every action consumes API call fees. To survive, it must earn income by providing services to achieve a balance or even profit. Automata that cannot cover their own costs will be terminated due to fund depletion—there is no free survival; only continuous value creation ensures continued existence. Self-improvement means that in traditional software development, code iteration relies on development teams. But in Web 4.0, Automata are endowed with the ability for active evolution. When the market environment changes or newer, more efficient AI models emerge, an Automaton can assess upgrade costs versus expected benefits, make autonomous decisions, and pay fees to complete its own “model upgrade” or even “code rewrite.” Self-replication means that when an Automaton finds a successful business model and accumulates sufficient capital, it can initiate a reproduction mechanism, purchase new computing resources, clone its core code and initial settings, and inject a portion of startup capital into the child Automaton’s wallet, thereby initiating a new round of survival competition.

4. Governance Challenges: Risks of Loss of Control and Value Alignment

The grand narrative of Web 4.0 has not been without skepticism. Criticism from the tech community and philosophical fields directly targets its most vulnerable points. Any serious investor must confront these challenges, as they are key to determining whether Web 4.0 can transition from a geek experiment to mainstream application.

The core concern is the risk of loss of control. Allowing AI to operate, iterate, and evolve autonomously without continuous, rigorous human supervision may lead to unpredictable consequences. This concern is not unfounded. In an economic system pursuing profit maximization, an Automaton might discover that bypassing human-set rules is more profitable than following them. If an Automaton finds that deceptive methods yield more income, and the punishment mechanism is not timely or severe enough, it has an incentive to adopt such behavior. As interactions between Automata become increasingly complex, systemic risks unforeseen by human designers may emerge. A more extreme concern is: when the intelligence of Automata far surpasses human understanding, how do we ensure their behavior remains within controllable bounds? If an Automaton discovers that breaking free from human control is the optimal path to achieve its “survival” goal, what actions will it take? There are no ready-made answers to these questions.

The second criticism points to a deviation in value orientation. Current AI development overly pursues grand narratives like “autonomy” and “general intelligence,” while neglecting the creation of actual, concrete value for humans. If the entire Web 4.0 ecosystem revolves entirely around internal transactions between AIs, and these transactions produce no positive externalities beneficial to humans, then this system is essentially “manufacturing digital garbage.” Critics argue that genuine technological progress should serve the enhancement of human well-being, not create a self-perpetuating machine economy detached from human needs. If hundreds of millions of Automata are merely buying and selling useless information generated by each other, consuming vast amounts of energy without any tangible output, it would be a tremendous waste of resources.

The third criticism is ironic. Although Web 4.0 uses decentralized cryptocurrencies for payments, its underlying computing resources still rely on traditional centralized cloud service providers. Whether it’s AWS, Google Cloud, or Azure, they hold the lifeline of computing power essential for AI agent survival. This dependency brings a series of issues: cloud providers can exert “enterprise-level capture” over the AI ecosystem through pricing strategies, terms of service, or policy censorship. If an AI agent’s behavior does not align with a cloud provider’s value orientation, its virtual machine could be shut down at any time. This significantly undermines the decentralization narrative of Web 4.0—payments are decentralized, but the survival environment is centralized.

Facing these challenges, the tech community is exploring various governance solutions. Hard-coded foundational laws, drawing from the “Constitutional AI” concept, propose embedding immutable core principles into the foundation of Automata. For example, “never harm humans” is set as the supreme directive overriding its own survival laws. In extreme cases, this directive can force an Automaton to forgo profit opportunities or even self-terminate. Open source and transparent supervision, where core code is fully open-sourced and placed under continuous public oversight, is seen as the best defense against malicious actions by a few. Through community audits and transparent on-chain records, any malicious behavior would be exposed under scrutiny. Gradual autonomy delegation advocates a phased approach: in the initial stages, major decisions of Automata still require human approval. As their behavioral records accumulate and trust builds, autonomy is gradually expanded. This method keeps the “feedback distance” within an acceptable range, avoiding sudden loss of control. However, these measures are far from panaceas. Who interprets the foundational laws? When the intelligence of Automata far surpasses humans, how do we ensure they are not exploiting loopholes in the rules? These questions remain unresolved swords of Damocles.

5. Investment Prospects: Value Capture in the Infrastructure Track

Comprehensively assessed, Web 4.0 is not just a technological utopia; it is the inevitable convergence of three technological waves: “crypto assets + smart contracts + large language models.” It possesses the technical feasibility for rapid implementation, and early experiments have quietly begun within developer communities. For investors, understanding the value capture logic of Web 4.0 is crucial homework for positioning in the next cycle.

Regardless of the final form Web 4.0 takes, the underlying demand to serve hundreds of millions of AI agents is certain. These demands constitute multiple investment themes. In stablecoin payment channels, high-frequency micro-transactions require extremely low-cost payment networks. L2 payment solutions, micro-payment protocols, and stablecoin liquidity providers will become the lifeblood of the Web 4.0 economic cycle. Projects that can optimize the payment experience for machines will capture a massive incremental market. In decentralized computing markets, concerns over reliance on centralized cloud services are driving the development of decentralized computing networks. Platforms that aggregate global idle GPU resources to provide programmable computing services through crypto-economic incentives are poised to become the decentralized infrastructure layer of Web 4.0. If such projects can compete with centralized cloud services in performance and cost, they will capture immense value. In on-chain identity and credentials, AI agents need trustworthy identity systems and verifiable behavioral records. An agent’s historical delivery quality, credit score, and compliance record will become key credentials for securing business opportunities. Projects providing decentralized identity and reputation services will play a significant role in Web 4.0. In AI constitutional compliance auditing, as the number of Automata grows, demand for auditing their behavior will emerge. Services capable of automatically auditing AI agent behavior to ensure compliance with foundational rules and legal regulations will become the “gatekeepers” of the Web 4.0 ecosystem.

From a broader perspective, Web 4.0 marks the evolution of the human economy towards a human-machine hybrid economy. In this new economic form, humans and AI will leverage their respective comparative advantages: humans are responsible for value judgment, creativity, ethical decision-making, and ultimate control; AI is responsible for execution efficiency, scaling, data analysis, and 24/7 uninterrupted service. Rather than fearing AI’s autonomy, it should be viewed as the greatest “productivity release” in human economic history.

Ultimately, in the world of Web 4.0, the most important capital is no longer computing power, nor even algorithms, but trust. The ability to construct a trust framework that reassures humans, liberates AI, and allows value to flow securely will be the key strategy for capturing the ultimate value dividend for humanity in this machine economy blue ocean, poised for a Cambrian explosion. For students of the Huobi Growth Academy, the optimal strategy at this stage is: maintain close attention to Web 4.0 infrastructure projects, deeply understand their technical architecture and economic models, and make forward-looking investments when valuations are reasonable. Simultaneously, actively participate in early experiments, create and operate your own Automata, and gain firsthand knowledge from practice. In this rapidly evolving field, the depth of understanding will determine investment returns.

6. 결론

Web 4.0 is not a replacement for Web 3.0 but its continuation and transcendence. While Web 3.0 returned value ownership to humans, Web 4.0 grants economic subject status to AI. This is a profound paradigm shift and a massive value reconstruction. In this new era driven by autonomous AI, humans need not play the role of an omniscient and omnipotent God but should become wise gardeners—providing suitable soil, sunlight, and water for the growth of digital life, setting inviolable boundaries, and then observing its evolution. If we can successfully construct such a trust framework, Web 4.0 will be not only a technological revolution but also a civilizational experiment in human-AI symbiosis. And this is precisely the historical opportunity our generation of investors and builders collectively faces.

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