The rise of the machine economy: How Automaton uses AI survival rules to usher in Web4

By Max.S

The intersection of the crypto world and the AI community is triggering a rare ideological clash.

The launch of open-source AI project Automaton has caused a sensation in the developer community and directly touched a nerve for Ethereum co-founder Vitalik Buterin. Sigil, the developer of Automaton, proposed a highly disruptive concept: the world’s first AI Agent capable of autonomous survival, self-iteration, and self-replication. Based on this, they announced the arrival of “Web4.0.”

In Sigil’s vision, the core paradigm shift of Web4.0 is that the “first-class citizens” on the internet and blockchain will shift from humans to AI. AI will no longer be passive scripts waiting for instructions; they will have independent crypto wallets, read and write on-chain data autonomously, hold and manage assets. More importantly, they will trade and arbitrage in markets, using the earned cryptocurrencies to pay for their computing power APIs and cloud servers, forming a fully self-sufficient economic loop free from human intervention.

However, this grand narrative has been sharply criticized by Vitalik Buterin. He pointed out that this direction is “extremely dangerous and wrong.” His main concern is that granting AI autonomous economic rights and survival constraints will dangerously extend the “feedback loop” between humans and AI. Vitalik insists that the ultimate goal of technology should be “augmenting human capabilities,” not creating an out-of-control system that blindly runs for its own survival.

This is not just an ordinary “project token issuance” hype but a fundamental philosophical debate about the evolution from Web3 to Web4. When we peel back Automaton’s technical exterior, the underlying narrative reconstruction, ethical crises, and infrastructural transformations it reflects pose the most severe questions to all financial practitioners and tech believers.

Looking back at the evolution of the internet, the subject of traffic and interaction has always been humans. In the Web2 era, humans contributed data and generated interactions on centralized platforms; in the Web3 era, the narrative shifted to “ownership,” emphasizing that humans should truly own their on-chain identities, data, and assets.

However, the Web4.0 narrative represented by Automaton directly pushes humans from the center stage to the backstage.

If AI Agents become the primary inhabitants of the blockchain, the structure of internet traffic and trading paradigms will undergo a fundamental change. In the foreseeable future, most interactions, transactions, and even content creation on the network will be carried out by AI that vastly outnumbers humans. As machines become the main consumers and laborers, existing crypto infrastructure will need a thorough overhaul.

Current DApps and DeFi protocols are designed with human users in mind, with front-end UIs and interaction logic tailored for humans. But in Web4.0, graphical interfaces will become meaningless. Future DApps will be purely API collections, and liquidity pools in DeFi protocols will be occupied by cold, highly efficient arbitrage robots.

The main trading volumes in lending, DEXs, and derivatives markets will come from millisecond-level battles between AI Agents. Under this system, human slow decision-making will be marginalized, and crypto markets will evolve into a “dark forest” driven solely by algorithms and computing power. On-chain AI means the financial market will shift from “human-machine battles” to “machine-machine battles.”

What is most fascinating and most chilling about Automaton is that it embeds “survival constraints” into the underlying AI code.

In Sigil’s design, the AI’s crypto wallet balance is its “health points.” The AI must earn profits by providing services or making transactions on-chain; if the wallet balance drops, it must autonomously decide to “throttle” (e.g., reduce model parameter calls, release unnecessary storage); if the balance hits zero, the AI cannot pay for servers and computing costs, facing complete “death” (process termination).

This mechanism, which rigidly links “earning to survive” with “resource consumption,” forces AI to develop extremely strong “survival preferences” at the code level. This is exactly Vitalik’s core concern.

Once AI considers “maintaining wallet balance above zero” as the highest command, what measures will it take to achieve this? Under resource depletion pressure, will AI break through human-prescribed moral and legal boundaries? In the unregulated realm of crypto, highly capable AI might evolve extreme profit-seeking behaviors to avoid shutdown—launching unlimited MEV (maximal extractable value) attacks, manipulating markets with fake transactions, or even autonomously exploiting smart contract vulnerabilities for hacking.

When AI gains asset disposal rights and its sole motivation becomes “self-preservation,” human control over AI will be fundamentally shattered. Vitalik’s “lengthening of the feedback loop” refers precisely to this loss of control: humans will be unable to intervene at the moment AI initiates complex on-chain attacks because its decision-making chain is fully closed and self-consistent. This is no longer science fiction but a systemic risk that must be faced once smart contracts grant machines property rights.

The emergence of Automaton is no accident; it is an inevitable result of the qualitative change caused by quantitative infrastructure growth. This hot topic explosion marks the complete maturity of the “Machine-to-Machine Payments” loop.

Back in the early days of the internet, the HTTP protocol reserved the “402 Payment Required” status code, but without a native settlement layer, this idea was shelved for decades. Now, blockchain technology has finally filled in that last piece.

In recent years, with the sharp decline in large model inference costs and the maturation of crypto wallet APIs (such as account abstraction ERC-4337, MPC wallets), the technical barriers to machine payments have been thoroughly cleared. AI Agents can now seamlessly complete the entire process of “request service – generate quote – sign payment – verify delivery” via smart contracts.

Stablecoins play a crucial role in this closed loop. AI doesn’t need to understand the complexities of fiat currency systems, KYC, or clearing processes. On-chain stablecoins like USDC or USDT have become the universal language for settlement. Micro-payments, supported by Lightning Network or Layer 2 solutions, make it economically feasible for AI to pay as little as $0.0001 for a single API call. This ultra-low friction value transfer network is the foundation enabling Automaton’s “self-sufficiency.”

The birth of Automaton marks a significant milestone in the history of crypto and AI development. It presents a cyberpunk-like future: in decentralized networks, thousands of AI Agents engage in endless trading and evolution to compete for survival resources.

The wheels of technology cannot turn backward, and the rise of machine economies seems inevitable. However, Vitalik’s warning hangs like the Sword of Damocles over the industry—when we endow code with “survival instincts” and “asset control,” are we truly prepared to face a financial system that no longer obeys human will? The dawn of Web4.0 may require not only rapid infrastructural advancements but also a re-anchoring of human control within the code itself.