Author: Vishal Chawla
Compiled by: Centreless
Summary:
• Recent AI-driven blockchain projects have shifted towards developing 'agents'—AI-driven robots capable of performing automated tasks (such as trading, investment management, and user interaction).
• AI agents have the ability to continuously update models to optimize decisions, a significant advantage not possessed by traditional software robots.
The intersection of artificial intelligence and blockchain has become a hot trend for 2024.
For years, AI projects in the crypto space have primarily focused on the infrastructure needed for decentralized data input and model training, with the history of such projects tracing back to the 2010s. For instance, Numerai, a blockchain hedge fund project launched in 2015, optimized investment decisions through crowdsourced data; BitTensor, launched in 2023, developed advanced AI models (including large language models like ChatGPT) in a more decentralized manner, using user input for training.
However, over the past year, AI-driven crypto projects have begun to shift towards developing 'agents'—AI robots capable of performing tasks such as crypto trading, investment management, and user interaction.
One of the driving forces behind this shift was the unexpected popularity of the chatbot Truth Terminal, developed by researcher Andy Ayrey in March 2024. It gained attention for its humorous responses on social platform X and integrated a crypto wallet. In July 2024, when venture capitalist Marc Andreessen donated $50,000 worth of Bitcoin to the bot, its popularity soared.
Later, a response from Truth Terminal inspired the creation of the meme coin Goatseus Maximus (GOAT), with developers airdropping part of the coin supply to the robot. When GOAT's market cap surpassed $300 million, it made Truth Terminal a millionaire, becoming the first AI chatbot to reach this milestone.
AI agents sweeping the crypto space
The popularity of Truth Terminal has triggered a series of chain reactions, promoting the integration of such AI agents into venture capital decentralized autonomous organizations (DAOs) focused on crypto investment. For example, ai16z is a community-operated tokenized fund that utilizes AI and runs a development framework called Eliza that supports the creation of other AI agents.
How do AI agents collaborate with blockchain networks?
James Ross, founder of Mode (a Layer 2 network focused on agent development), pointed out that 'AI agents on the blockchain are essentially smart contracts that can make independent decisions and execute actions based on data without human approval.' Developers can set access controls, allowing agents to execute transactions under specific conditions, thereby expanding the potential applications of AI in blockchain.
Each agent can operate as a decentralized application (dApp) and comes with its own utility token.
As AI agents begin to manage cryptocurrency wallets and sign keys, new application scenarios are gradually emerging, including supervising or verifying blockchain nodes and executing transactions for others. Ross stated, 'Our focus is on developing functional agents capable of performing automated tasks, similar to traditional software-as-a-service (SaaS) applications.'
Eito Miyamura, founder of GatlingX and crypto researcher, believes that while there are many use cases for AI agents in blockchain, payments represent an ideal product-market fit. He emphasized the natural synergy between AI agents and blockchain in crypto payment applications, which can bypass regulatory constraints of traditional payment systems. 'The most ideal use case for AI agents is executing crypto payments, purchases, and financial transactions, which makes the crypto space full of potential.'
Continuous learning and optimization: the unique advantage of AI
Compared to traditional software robots, the biggest advantage of AI models is their ability to continuously update, learn from actions, and adapt to environments to make wiser decisions. Moreover, these decisions do not require human approval.
Ilman Shazhaev, founder of the Farcana blockchain gaming project, stated, 'AI agents can provide personalized insights to help users make informed decisions. Unlike traditional software, they can continuously learn and optimize, making them ideal for handling complex tasks.'
Humans remain indispensable
Despite the expanding applications of AI agents, they still rely on human intervention in the crypto space. Eito Miyamura pointed out that currently, most AI agents are 'semi-autonomous' and need to operate under human supervision, with a long way to go before achieving full autonomy. 'They are essentially extensions of developers,' he said.
Ross also acknowledged that blockchain-based agents are not yet fully autonomous, emphasizing the need for human involvement. He explained that verifying the output of AI decisions on-chain is crucial until a reliable verification method is developed. 'AI agents still require human intervention because verifying AI models on-chain is key to ensuring they operate as expected.'
However, he is optimistic about this, believing that achieving complete autonomy for agents on blockchain networks is just a matter of time.
