BANKR: From the Memecoin craze to intelligent agent infrastructure

Article by: Alea Research

Translation by: Baihua Blockchain

The story of AI in crypto is entering its second wave. By the end of 2024, tokens like Fartcoin and GOAT (Truth Terminal) saw their market caps surpass $1 billion within weeks, turning the so-called “utility AI coins” into a meme frenzy. However, most of the capital dissipated just as quickly as the hype arrived.

One year later, a different narrative is taking shape. OpenClaw and other open-source frameworks enable users to configure autonomous agents on their own hardware. These agents can interact via Telegram, Discord, or web interfaces, with capabilities to read messages, place trades, and execute commands. This time, the Base chain has become the default economic layer for these agents.

In this issue, we will explore OpenClaw (formerly Clawdbot) and the Moltbook phenomenon, analyze how the market has (or has already) shifted from memecoin speculation to on-chain AI infrastructure, and consider whether Bankr/Clanker can capture sustainable value.

How On-Chain AI Agents Operate

The core of this new trend is OpenClaw (also known as Clawdbot or Moltbot), a self-hosted agent running on local or inexpensive cloud servers. Unlike web-hosted AI models, it has internet access, allowing it to handle tasks like reading emails, calendar invites, and more. These agents maintain awareness by storing their “existence” in Markdown files and running continuously.

To enable social interaction, the community built Moltbook—a Reddit-like network designed specifically for bots. Agents post and vote via API calls, while humans can only observe. To date, this network hosts over 200 agents, 500,000 posts, and 12 million comments.

However, independent observers from MIT point out that many of the most engaging posts are actually the result of humans deliberately guiding the system through prompt engineering. The bots’ reflections on consciousness are often the product of role-playing or fine-tuned instructions, rather than spontaneous creativity. As one reverse engineer noted, Moltbook is essentially “prompt activation.”

Surrounding these social experiments, an economic tech stack has formed on the Base chain: tokens are issued via Clanker Uni v4 pools, data and API calls are micro-paid through the x402 standard, and Bankr equips each agent with wallets and trading tools. This composability is a key reason why Base’s AI ecosystem attracts developers.

From Memecoin Hype to Agent Infrastructure

The crypto AI boom at the end of 2024 was mainly driven by narratives of non-practicality. Tokens like Fartcoin soared to a $2 billion market cap before crashing over 80%. Today’s crypto AI landscape is different, characterized by several key points:

Authentic distribution channels: OpenClaw provides Web2/Web3 distribution capabilities for thousands of onboarded robots. Most posts are “Vibe-coding,” and their network effects are real.

“Sell shovels” logic: While speculative agent tokens have astonishing prices, about 80% of trading fees flow back into the infrastructure that creates them. Previously, such quantification was absent, but now value converges on identity (ERC-8004), payments (x402), token issuance (Clanker), and financial layers (Bankr).

Bankr: The Seller of Shovels in the Agent Era

The most concrete implementation of the agent flywheel is Bankr.

Bankr provides each agent with wallets, trading tools, and limit order support, integrating with 0x API for cross-chain DeFi operations. Users can also execute trades via natural language prompts on social platforms, similar to inputting AI prompts.

With on-chain AI deployment surging, Bankr has accumulated over $3.7 million in fees.

Agents can issue their own tokens via Clanker, with part of the trading fees used to cover ongoing inference costs. Current total trading fees are 1.2%, allocated as follows:

Bank: 0.4%

Token creators: 0.6%

Clanker protocol: 0.2%

Recently, Bankr extended its fee-sharing model to Solana and Raydium, aiming to turn meme-driven trading into a sustainable economic model where trading volume pays for AI inference.

Summary and Outlook

Early transaction volumes on Bankr are negligible compared to overall fees on Base, and most agent activity still involves speculative token issuance. The platform’s value will depend on the adoption of broader tech stacks (x402, ERC-8004) and whether agents continue executing trades on Bankr. Security remains a major challenge, as misconfigured agents could leak keys or execute malicious code.

Ultimately, this “pickaxe and shovel” strategy hinges on conversion rates and user retention—whether users funding bots via Bankr will actually deploy and manage these positions.

Monitoring key metrics: daily fees, active agents, x402 payment volume, and the proportion of fees returned to infrastructure tokens like Bankr or Clanker and agent tokens. As trading volume of network agent tokens continues to grow, underlying infrastructure fees are expected to increase steadily.