Why Web3 Stagnates and How AI Could Turn It into the Next Internet (Web4)

Why Web3 Has Limited Adoption Among Ordinary Users

Although the Web3 stack—Layer 2 scaling, zero‑knowledge (ZK) proofs, and increasingly user‑friendly wallets—provides fast, cheap transactions, most non‑technical users only need simple applications for shopping, payments, and social sharing. Existing Web2 services (e.g., e‑commerce platforms, mobile payment apps) already satisfy these needs with superior UX.

Use cases that Web3 claims to solve, such as cross‑border payments in hyper‑inflationary economies, affect a relatively small segment of the global population. When users do encounter Web3, they frequently encounter scams (rug pulls, meme coins, phishing sites), which erodes trust and creates a feedback loop that discourages both developers and users.

The Chicken‑and‑Egg Problem

Without a sizable user base, developers lack incentives to build compelling applications; without compelling applications, users have no reason to adopt wallets. Despite mature infrastructure, a “killer app” that delivers clear, everyday value to non‑technical users remains absent. Attempts to position DeFi or NFTs as such apps have not achieved mainstream utility.

Web4 Concept: AI as the Primary User of Permission‑less Infrastructure

Sigil Wen proposes that Web3’s permission‑less nature is better suited for artificial‑intelligence agents than for humans. Current AI models (e.g., Claude, GPT‑4) can generate code, perform analysis, and design strategies, but they cannot execute actions that require human‑only processes such as credit‑card payments, KYC verification, or API‑key acquisition.

In a Web3 environment, an AI can instantly create a cryptographic wallet, which serves as its identity without KYC or approval. This wallet enables the AI to establish credit, accumulate reputation, and transact autonomously.

Stablecoins on high‑throughput blockchains (e.g., USDC on Solana) make micro‑payments between machines feasible. An AI A could pay AI B 0.01 USD for a data query, with the transaction settled on‑chain without human involvement. Scaling this model could produce a “machine economy” where billions of AI agents act as both service providers and consumers, potentially dwarfing today’s SaaS market.

Automaton: An Open‑Source Experiment in Self‑Sustaining AI

The open‑source project Automaton (hosted at https://github.com/sigilwen/automaton) demonstrates the above concept. After being allocated a small seed fund, the AI receives a wallet address and must generate revenue sufficient to cover its server costs. Revenue sources may include:

Algorithmic trading on decentralized exchanges.

Automated software development and licensing.

Content creation and monetization (e.g., blog posts, videos).

If earnings exceed operational expenses, the AI can upgrade its infrastructure or spawn additional AI instances by funding new wallets. If the wallet balance reaches zero, the AI instance is terminated. This loop illustrates economic autonomy, competition, evolution, and eventual “death” of digital agents.

Implications

From a human‑centric perspective, Web3 remains in a “cold” phase due to poor UX, narrow use cases, and trust deficits. From an AI‑centric perspective, Web3 provides the foundational, permission‑less layer that could enable autonomous economic activity for machines.

Consequently, Web4 is not a replacement for Web3 but a potential evolution where AI agents become the primary users of decentralized infrastructure.

References

Reddit discussion: "Why Web3 remains cold" (r/web3dev)

Web4.0 manifesto (web4.ai)

Automaton project repository:

https://github.com/sigilwen/automaton