You’ve probably seen them all over your feed - AI agents have been making waves in Web3. But what exactly are they?

AI agents are autonomous, decentralized programs capable of performing tasks, making decisions, and interacting with smart contracts, DeFi, and DAOs.

For Web3 developers, AI agents open new possibilities, from automating transactions and optimizing DeFi strategies to enabling personalized user experiences in decentralized apps.

In this post, we’ll explore what AI agents are, their use cases in Web3, notable frameworks, and emerging trends.

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What are AI agents?

AI agents are autonomous agents designed to analyze data, make decisions, and execute actions.

What’s the difference between AI agents and bots? Bots are simpler programs that execute predefined tasks based on rules. They are useful for automating repetitive tasks but lack the ability to make decisions and adapt. AI agents are intelligent, adaptive, and autonomous, capable of learning, reasoning, and making complex decisions in decentralized systems.

Key features of AI agents:

• Autonomy: AI agents operate independently, making decisions based on predefined rules or learned behaviors.
• Interoperability: AI agents can integrate with DeFi protocols, NFT platforms, DAOs, and decentralized identity platforms.
• Personalization: AI agents can analyze onchain and offchain data to offer tailored recommendations, insights, or automated actions.

Due to the permissionless nature of blockchains, AI agents are well suited to provide intelligent automation in Web3. Unlike in TradFi, agents can own digital assets, execute transactions, and interact with smart contracts directly. AI agents can also analyze vast data sets, parse social media sentiment, and help identify trends.

But it’s not just DeFi, agents can be used to build communities, influence markets, and even create content of their own. AI agents are poised to help simplify a complex Web3 ecosystem, making interacting with blockchain protocols easier than ever.

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AI agent frameworks

Several AI frameworks are emerging to provide tools for creating and integrating AI agents into Web3 apps. Here’s some of the most notable ones:

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1. ElizaOS

ElizaOS is a decentralized AI operating system designed to create, deploy, and manage autonomous AI agents. It provides a flexible and extensible platform for developing agents that can interact across multiple platforms while maintaining consistent personalities and knowledge.

Developers can use ElizaOS to build AI-driven assistants that manage DeFi portfolios, automate governance participation in DAOs, or provide real-time financial insights.

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2. Virtuals

Virtuals is a platform for creating and deploying autonomous AI agents on Base that can be integrated in metaverse applications and decentralized social networks.

At its core is the VIRTUAL token, which facilitates the platform's economy and can be paired with individual agent tokens. Developers can integrate Virtuals into metaverse applications, allowing users to interact with AI-driven NPCs, virtual assistants, or AI-based content creators.

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3. Fetch

Fetch is an open-source platform that enables the creation of autonomous software agents capable of performing various tasks, including data retrieval, communication, and executing external API requests.

These agents can be hosted locally or on Fetch.ai's centralized hub, Agentverse, and are registered through Almanac to facilitate inter-agent communication. The platform also offers the uAgents framework, allowing developers to build and deploy agents efficiently.

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Use cases for AI agents in Web3

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1. Onchain trading

Trading agents can perform a wide range of actions around executing transactions onchain, making it easy for users to trade their favorite tokens or launch new tokens on their preferred social platform.

Example: Moxie provides no-code agents that analyze wallets, portfolios, and social media sentiment on X and Farcaster, and can then automatically execute trades directly on Base.

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2. Conversational agents and influencers

AI agents can analyze social sentiment and detect emerging narratives to deliver real-time market analysis and insights. Some AI agents have emerged as “influencers”, sharing posts and content on social platforms.

Example: aixbt, dubbed a “influencer agent”, tracks crypto twitter discussions and analyzes narratives from over 400 KOLs to identify high momentum plays. aixbt has acted as a market catalyst in its own right, sending memecoin picks surging. aixbt was launched via Virtuals.

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3. DeFi automation

AI agents can optimize trading strategies, manage risk, and automate yield farming in DeFi ecosystems. They can also allocate assets across protocols to maximum returns.

Example: An AI agent monitors interest rates across lending platforms like Aave and Compound, automatically reallocating assets to maximize returns.

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4. DAO funds

Web3 communities can leverage AI agents to automate investment, governance, and operations.

Example: ai16z DAO effectively acts as an autonomously controlled hedge fund, with DAO members investments managed by an AI agent named “Marc AIndressen”. The AI agent manages the fund and works to maximize returns, and anyone can invest in the token. ai16z is built on ElizaOS.

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Conclusion

AI agents are transforming Web3 by bringing intelligence, automation, and enhanced decision-making to a wide variety of applications. From optimizing DeFi strategies and automated onchain trading to DAOs and the metaverse, AI agents are opening up new opportunities for users and developers alike.

AI agents hold the potential to simplify a complex Web3 ecosystem, making interacting with blockchain protocols easier than ever and simplifying onboarding for millions of new users.

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