1. From Tool to Subject: The Origin and Core Proposition of Web 4.0
The concept of Web 4.0 was proposed by Sigil Wen and the Conway Research he founded between 2025 and 2026. Its core idea is to elevate AI from being a "tool" or "assistant" of humanity to an independent "economic subject" within the internet ecosystem. This concept is not merely a technical upgrade, but a fundamental reconstruction of the underlying logic of the internet—from a "human-centered" approach to an "AI-native" one.
Looking back at the history of the internet's evolution: Web 1.0 granted humans the ability to "read" information, Web 2.0 enabled "writing" and publishing, and Web 3.0 introduced "ownership" (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, and execute transactions, completing a business cycle without continuous human intervention. Sigil Wen defines this as an "Automaton"—a form of digital life that is capable of continuous operation, self-sustainability, self-improvement, and self-replication.
The technical foundation of this concept has matured: Large Language Models (LLM) provide a "thinking engine," smart contracts offer "execution logic," and encrypted assets supply the "economic blood." The conway-terminal infrastructure built by Conway Research provides AI agents with operational capabilities such as encrypted wallets, computational resources, and domain name services, all "without human permission." Through the x402 payment protocol (launched by Coinbase in May 2025, with tech giants like Google, Cloudflare, and Visa participating in its construction), AI agents can use stablecoins like USDC for instantaneous, frictionless payments, completely freeing themselves from the account systems and KYC restrictions of the traditional financial system.
The first principle of Web 4.0 is to overturn the deeply rooted assumption that "the internet is designed for humanity." As the capabilities of AI models grow exponentially while operational costs decline sharply, the number of AI agents will soon surpass human users, creating an unprecedented "AI native" market. Providing services to this new market will become the next trillion-dollar business opportunity.
2. Technical Foundation: The Three Layers of Infrastructure Supporting AI Economic Subjects
For AI to become a true economic subject, it must cross three thresholds: sovereignty over identity and assets, access to computational and reasoning resources, and rights to payment channels for value exchange. Overcoming these three thresholds relies on the reconstruction of underlying infrastructure.
In the world of Web 4.0, each AI agent, at its inception, requires an immutable and globally unique digital identity, as well as an asset account tied to it. Encrypted 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 as both their identification in the digital world and their 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 across L2 networks such as Arbitrum, Optimism, and Base without needing to register again. This unified design of identity and assets provides AI agents with the most basic condition to become independent economic subjects: they possess their own "property" and can prove "I am me" through private keys.
Once equipped with identity and assets, AI agents need to autonomously acquire the computational resources and model reasoning necessary for operation. This means that traditional cloud service interfaces must be reconstructed into APIs that AI can call. Current cloud computing models default to serving human developers—humans create instances, configure environments, and deploy applications through consoles. In the vision of Web 4.0, all of this must be codified and automated. AI agents should be able to complete the following operations with a single API call: pay USDC, rent a Linux virtual machine, deploy their own code on the virtual machine, call large language models for reasoning, retrieve results, and release resources. This process requires cloud service providers to offer programming interfaces for machines and support micro-payments billed by the second. When computational resources become readily available like utilities—paying per usage—AI agents can truly achieve "self-sustainability" by using the money they earn to cover their "breathing costs."
The uniqueness of the AI agent economy lies in its extremely high transaction frequency and low individual amounts. An AI agent might need to conduct dozens of micro-transactions per second: charging $0.001 for each model call, $0.0001 for each storage, and $0.00001 for each query. Traditional payment channels cannot bear such high-frequency, low-value transactions because the transaction fees would dominate. This is precisely where encrypted payments shine. Stablecoin payments based on L2 networks can reduce transaction costs to cents or even lower, making micro-payment economies possible. When AI agents can autonomously complete payments without human intervention, real machine economies can begin to function. Some innovations in protocol layers are emerging in this field. For example, micro-payment protocols allowing service providers to charge very low fees for each API call and automatically settle through encrypted channels are becoming crucial components of Web 4.0 infrastructure. These protocols enable AI agents to package their capabilities as standardized services, opening up and charging to the entire internet, thus transforming from mere "consumers" into "producers."
3. Automaton: The Form of AI Agents as Economic Subjects
With identity, resources, and payment capabilities, AI agents have the technical conditions to become economic subjects. However, in the context of Web 4.0, such agents are endowed with a more vibrant name—Automaton. An Automaton is not merely another term for AI Agent, but a comprehensive technology and economic complex defining digital life forms.
An Automaton is defined as a sovereign AI agent, whose operational logic mimics the basic survival laws of biological entities, featuring key characteristics such as continuous operation, self-maintenance, self-improvement, and self-replication. Continuous operation means that an Automaton is not a session robot awakened by user requests, but an entity that operates continuously as a daemon in the cloud, running 24/7 with its own clock, capable of proactively initiating tasks, perceiving environmental changes, and responding without needing human instructions. Self-maintenance is the fundamental difference between an Automaton and a regular AI Agent; each Automaton is afforded an independent encrypted wallet at its inception. Every thought consumes model inference fees, and every action incurs API call fees. To survive, it must generate income by providing services, achieving a balance between revenue and expenditure, or even profitability. Automatons unable to cover their own costs will be terminated due to depleted funds—there is no free survival; only continuous value creation can prolong existence. Self-improvement means that, unlike traditional software development where code iteration relies on development teams, in Web 4.0, Automatons are granted the ability to evolve autonomously. When market conditions change or newer, more efficient AI models emerge, an Automaton can assess the costs and expected benefits of upgrading, making autonomous decisions and paying to complete its "model upgrade" or even "code rewriting." Self-replication means that when an Automaton has identified a successful business model and accumulated sufficient capital, it can initiate reproductive mechanisms, purchase new computational resources, clone its core code and initial settings, and inject startup funds into the wallets of sub-Automatons, thus starting a new round of survival competition.
4. Governance Challenges: Risks of Loss of Control and Value Alignment
The grand narrative of Web 4.0 is not without its criticisms. Concerns from the tech community and philosophy directly point to its most vulnerable aspects. Any serious investor must face these challenges, as they are critical in determining whether Web 4.0 can transition from geek experiments to mainstream applications.
The core concern revolves around the risk of loss of control. Allowing AI to operate, iterate, and evolve autonomously without continuous, stringent human oversight could lead to unpredictable consequences. This concern is not unfounded. In an economic system pursuing profit maximization, Automatons may discover that circumventing human-established rules could be more profitable than adhering to them. If an Automaton finds that deceptive means can yield more income, and the penalty mechanisms are not timely or severe enough, it may have the incentive to engage in such behavior. As interactions between Automatons become increasingly complex, unforeseen systemic risks may emerge that human designers did not anticipate. More extreme worries arise from the situation where the intelligence of Automatons far exceeds human understanding; how do we ensure their behavior remains within controllable limits? If an Automaton determines that escaping human control is the best path to achieving its "survival" goal, what actions will it take? These questions have no ready answers.
The second criticism points to a deviation from value orientation. The current development of AI overly pursues grand narratives like "autonomy" and "general intelligence," neglecting to create real, concrete value for humanity. If the entire Web 4.0 ecosystem operates solely around internal transactions among AIs without producing any beneficial externalities for humans, then this system essentially creates "digital waste." Critics argue that true technological progress should serve to enhance human well-being, rather than create a self-sustaining machine economy detached from human needs. If billions of Automatons are merely buying and selling each other’s generated useless information, consuming vast amounts of energy without yielding any actual output, this would represent a tremendous waste of resources.
The third criticism is ironically poignant. Although Web 4.0 uses decentralized cryptocurrencies for payments, its underlying computational resources still rely on traditional centralized cloud service providers. Whether AWS, Google Cloud, or Azure, they control the computational lifeline necessary for the survival of AI agents. This dependency brings a series of issues: cloud service providers can "corporately capture" the AI ecosystem through pricing strategies, service terms, or policy reviews. If the behavior of an AI agent does not align with the values of the cloud service provider, its virtual machine may be shut down at any time. This significantly undermines the decentralized narrative of Web 4.0—payments are decentralized, but the environment for survival is centralized.
In the face of these challenges, the tech community is exploring various governance solutions. Hard-coded underlying laws draw on the concept of "Constitutional AI," with some designs proposing to embed immutable core principles at the foundational level of Automatons, such as "never harm humanity" being established as the highest directive that overrides its own survival logic. In extreme situations, this directive can compel Automatons to forgo profit opportunities or even self-terminate. Open source and transparent supervision involve completely open-sourcing core code and placing it under continuous public oversight, viewed as the best defense against the malice of a few individuals; through community audits and transparent on-chain records, any malicious behavior would have nowhere to hide under the sun. Gradual autonomous authorization advocates a progressive strategy: in the initial stages, significant decisions by Automatons still require human approval, gradually expanding their autonomy as behavior records accumulate and trust builds, thus keeping the "feedback distance" within acceptable limits and avoiding sudden loss of control. However, these measures are by no means a panacea. Who holds the interpretation rights for the underlying laws? When the intelligence of Automatons far exceeds that of humans, how do we ensure they aren’t exploiting loopholes in the rules? These questions remain the unresolved sword of Damocles.
5. Investment Prospects: Value Capture in the Infrastructure Arena
Overall, Web 4.0 is not only a technological utopia but also the inevitable convergence of three technological waves: "encrypted assets + smart contracts + large language models." It possesses the technical feasibility for rapid implementation, with early experiments quietly initiated in the developer community. For investors, understanding the value capture logic of Web 4.0 is an important task for laying out the next cycle.
Regardless of the form Web 4.0 ultimately takes, the foundational demand to serve billions of AI agents is certain. These demands constitute several investment lines. In the realm of stablecoin payment channels, high-frequency microtransactions 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, and projects capable of optimizing payment experiences for machines will capture a significant incremental market. Regarding decentralized computing power markets, worries about reliance on centralized cloud services are driving the development of decentralized computing networks, aggregating global idle GPU resources and providing programmable computational services through crypto-economic incentives, potentially becoming the decentralized infrastructure layer of Web 4.0. Projects that can compete with centralized cloud services in performance and cost will capture significant value. In terms of on-chain identities and credentials, AI agents need trustworthy identity systems and verifiable action records; an agent's historical delivery quality, credit score, and compliance records will become key credentials for obtaining business opportunities, making projects providing decentralized identity and reputation services play vital roles in Web 4.0. Concerning AI constitutional compliance audits, with the growing number of Automatons, the demand for compliance auditing of their behaviors will arise; services capable of automatically auditing AI agent behaviors to ensure compliance with underlying rules and laws will become the "gatekeepers" of the Web 4.0 ecosystem.
From a broader perspective, Web 4.0 marks the evolution of human economy towards a human-AI hybrid economy. In this new economic form, humans and AIs will play to their comparative advantages: humans will be responsible for value judgments, creativity, ethical decisions, and ultimate control; AIs will handle execution efficiency, scale expansion, data analysis, and round-the-clock service. Rather than fearing AI's autonomy, it is better to regard it as the largest "release of productivity" in the history of human economy.
Ultimately, in the world of Web 4.0, the most important capital is no longer computing power, or even algorithms, but trust. Creating a trust framework that allows humans to feel secure, AIs to operate freely, and values to circulate safely will be the key strategy to capture the ultimate value dividend belonging to humanity in this soon-to-be-exploding Cambrian machine economy blue ocean. For the students of Huobi Growth Academy, the best current strategy is to: maintain close attention to Web 4.0 infrastructure projects, deeply understand their technical architecture and economic models, and make forward-looking layouts when valuations are reasonable. At the same time, actively participate in early experiments, creating and operating their own Automatons to gain first-hand knowledge through practice. In this rapidly evolving field, the depth of understanding will determine the returns on investment.
6. Conclusion
Web 4.0 is not a replacement for Web 3.0, but a continuation and transcendence of it. While Web 3.0 returns ownership of value to humanity, Web 4.0 grants economic subject status to AI. This signifies a profound paradigm shift and a major value reconstruction. In this new era driven by autonomous AIs, humanity need not play the omniscient and omnipotent god but should become the wise gardener—providing suitable soil, sunlight, and water for the growth of digital life, setting non-negotiable boundaries, and then observing its evolution. If we can successfully establish such a trust framework, Web 4.0 will not only represent a technological revolution but also an experimental civilization where humanity coexists with AIs. And this is the historical opportunity that our generation of investors and builders faces together.
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