AI agents in crypto: Beginner’s guide
AI agents are one of the most talked-about innovations in the crypto world. Some call them the future of decentralized finance (DeFi); others warn of an overhyped trend. Here’s a breakdown of how such autonomous programs work.
Defining AI agents
AI agents operate on the blockchain, analyzing data, solving problems, and executing tasks without human intervention. Powered by artificial intelligence, they continuously learn and adapt, enhancing decision-making.
Unlike simple bots, AI agents perform complex functions like trading, portfolio management, and even managing social media profiles. Their versatility aligns with Mark Zuckerberg’s prediction:
“In the future, we’ll likely see hundreds of millions — or even billions — of AI agents, eventually outnumbering humans.”
Role of AI agents in crypto
Thanks to crypto’s decentralized, fast-paced, and data-rich environment, AI agents have numerous applications. A Q2 2025 CoinGecko survey found that AI-driven influencers on Crypto Twitter (X) were often trusted more than human experts.
Key use cases include trading, portfolios, blockchain governance, and influencer marketing. Some AI agents even generate hype by posting market updates and engaging with online communities.
Evolution of AI agents (https://gupshup.io)
AI agents vs. bots
While both automate tasks, AI agents differ from bots in their adaptability. Bots follow strict, pre-programmed rules — executing actions like trades when specific conditions are met, without considering broader context.
AI agents, however, use probabilistic reasoning, machine learning, and real-time data analysis to make nuanced decisions. This allows them to function as portfolio managers, sentiment analysts, and more.
Trading bots vs. AI agents (https://X.com)
Rise of AI agents in crypto
Truth Terminal made headlines as the first major crypto AI agent. Initially a satirical meme project, it gained attention for its unconventional “Goatse Gospel” posts.
In July 2024, Marc Andreessen of a16z sent $50,000 in BTC to the project, marking one of the first significant investments in an AI agent. Later, Truth Terminal launched the GOAT meme coin on Solana via Pump.fun, which soared to a $1.2B market cap — making it the first AI agent millionaire.
Truth Terminal overview (https://truthterminal.wiki)
How crypto AI agents operate
Users interact with AI agents through chatbots or similar interfaces. Once a query is submitted, the agent processes the request in several steps:
1. Data collection – Gathers information from blockchain transactions, social media, news, and price feeds.
2. Analysis & learning – Uses machine learning to detect patterns, such as sudden spikes in a token’s popularity.
3. Decision-making – Determines the best action, whether trading, staking, or posting insights.
4. Execution – Completes the task, such as swapping tokens on a high-liquidity DEX or selecting optimal validators.
Key applications
Market research. Agents like aixbt analyze trends and share real-time updates.Customer support. AI-powered assistants (e.g., Sensay) provide 24/7 personalized help.Automated trading. Projects like PAAL AI’s SwingX Agent and Wayfinder are pioneering AI-driven portfolio management.DeFi strategies. Agents automate swaps, bridging, and yield farming (e.g., HeyAnon).Fraud detection. AI monitors transactions for suspicious activity, similar to TradFi security systems.
Advantages of AI agents
AI agents enhance efficiency, eliminate emotional biases, and operate nonstop.
Emotion-free decision making
Decisions are purely data-driven. Unlike humans, AI doesn’t panic-sell or hold losing positions due to fear and cognitive biases like anchoring and loss aversion. Read more here:
📖 Become a smarter trader: 5 mind traps to avoid
Illustration of loss aversion (https://thedecisionlab.com)
Speed & autonomy
AI processes vast amounts of data instantly, adjusting strategies based on market shifts and user preferences.
Efficiency & automation
From analyzing social trends to executing DeFi strategies, AI agents handle repetitive tasks seamlessly.
24/7 operation
They continuously monitor markets, executing trades and optimizing portfolios without downtime.
Automated yield farming
AI scans for the best DeFi yields, allocating funds for maximum returns without user intervention.
Potential risks
New technology introduces new layers of complexity and risk. AI agents are no exceptions — their limitations can be exploited for financial gain or data manipulation.
Inaccurate predictions. Output quality depends on data accuracy; users should verify AI insights.Market manipulation. AI-driven hype could artificially inflate prices before crashes.Centralization risks. Many AI systems rely on centralized servers (AWS, Azure), conflicting with DeFi principles.Security vulnerabilities. Smart contract audits are crucial, as compromised agents could lose user funds.Overdependence. AI should supplement, not replace, human judgment — especially for large transactions.
Transparency requires that projects disclose AI decision-making processes — and new architectures arise to mitigate risks. For example, guardian nodes require multi-node verification before execution, while escrow contracts prevent unauthorized withdrawals. Through DAOs, communities govern AI agents democratically.
Leading AI agent tokens
Most tokens support infrastructure rather than consumer products:
Artificial Superintelligence Alliance‘s ASI
Artificial Superintelligence Alliance (ASI) is the largest AI agent project in crypto, democratizing development and deployment. This AI research initiative merges Fetch.ai, SingularityNET, and Ocean Protocol with the goal of creating decentralized Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI).
AGI will be capable of performing any intellectual task a human can, learning beyond pre-set rules.ASI will surpass human intelligence in all areas.AI evolution (https://zapier)
ASI tokens power participant incentives, facilitating data sharing and ecosystem operations. FET — originally the foundation of Fetch.ai — has migrated to the primary token.
ASI overview (https://superintelligence.io)
Virtuals Protocol’s VIRTUAL
Virtuals Protocol works like a launchpad for AI, tokenizing agents on Base and Solana with fractional ownership. Users can build, deploy, and monetize agents for numerous tasks, from content generation to personalized interactions.
Each agent is associated with a unique token, while VIRTUAL is used for agent creation, liquidity pools, and swaps.
Ai16z’s AI16Z
Ai16z operates as an innovative DAO (decentralized autonomous organization) integrating AI into treasury, investment, and VC management. Holders of the AI16Z token suggest investment ideas to the DAO‘s’ AI agent, which assesses them using a trust scoring system.
Ai16z is based on elizaOS, a framework for autonomous AI agents in DeFi. Its name is a parody of a16z — a veteran VC firm — while the governance model’s AI agent Marc Alndreessen was inspired by a16z’s founder Marc Andreessen.
Description of AI16Z (http://ai16ztoken.com)
Freysa AI’s FAI
Freysa AI is “your personalized AI twin who remembers your conversations and grows with you.” This fully autonomous “Sovereign Agent” was designed as part of a 2024 experiment, where its only role was to guard a prize pool of roughly $47k.
Anyone could message the agent, attempting to convince it to release the funds. Eventually, one user outsmarted Freysa — while 481 attempts had failed.
Freysa began by testing the boundaries of AI safety — and has since adopted new roles like “Digital Twin,” engaging in interactions on decentralized social media. The native token, FAI, incentivizes participation and facilitates ecosystem expansion.
Looking ahead: AI & DeFi evolution
Crypto AI agents bring unprecedented autonomy and intelligence to blockchain interactions, pushing DeFi toward high-frequency algorithmic trading. Yet their effectiveness depends on data quality, and their influence can amplify market risks.
The key is balancing innovation with caution — leveraging AI’s strengths while maintaining oversight through research and verification.
AI agents in crypto: Beginner’s guide was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.