How to Build an On-Chain AI Agent with Smart Contracts

• There is a growing level of decision-making abilities and interactions of AI agents with applications and tasks without human assistance. 
• If such technologies are combined with blockchain technologies, AI agents will be able to do more than just process data; they will be able to communicate with smart contracts, conduct transactions, monitor the blockchain, and perform predefined tasks.
• An AI agent on-chain is an AI-based system capable of communicating with the blockchain via smart contracts and the blockchain itself. 
• The AI does not necessarily have to reside on-chain; in most real-world scenarios, the AI model will reside off-chain, whereas smart contracts will provide programmable execution.

Here is how you build one.

What Is an On-Chain AI Agent?

• The on-chain AI agent consists of an AI model along with blockchain-related applications. The AI model is responsible for tasks like interpretation of the data, decision-making, or figuring out what needs to be done. 
• Smart contracts then perform all those actions that are allowed to be executed according to the rules of the smart contract.
• For instance, an on-chain AI agent can be monitoring the decentralized finance protocol and analyzing the conditions of the market, executing a certain smart contract function if some conditions are satisfied.

Step 1: Define the Agent’s Purpose

Decide what your AI agent is going to do before writing any code.

One straightforward example would be the case of an AI that tracks token prices and interacts with a smart contract under specific circumstances. More sophisticated AI agents may handle treasury tasks, automate DeFi strategies, keep track of governance proposals, or work with DApps.

Specify these properly:

• What information your AI has access to
• What decisions your AI can take
• Which blockchain it will operate on
• Which functions it is able to call on a smart contract
• Which actions will need your approval

It is crucial since providing AI with unlimited transaction rights may pose serious security threats.

Step 2: Choose a Blockchain

Afterward, pick the blockchain that your smart contracts will run on.

Ethereum is often used since it has a well-developed smart contract ecosystem, but there are other blockchains that may provide various mixes of fees, speeds, and ecosystems like Arbitrum, Base, Optimism, and Polygon.

The decision should be based on the following criteria, among others:

• Fees
• Speed
• Smart contract compatibility
• Developer tools
• Liquidity and applications
• Security needs

Step 3: Build the Smart Contract

It is in the smart contract that the exact capabilities of the AI agent are specified.

For Ethereum-compliant systems, smart contracts are coded using a programming language called Solidity. Functions that enable a whitelisted address to do certain things can be included in the contract.

Instead of allowing an AI agent unlimited access to transfer funds, you can set restrictions like maximum amounts, certain tokens, destination addresses, or even time limits.

This is because there is a security limit that separates the decision-making capability of the AI from its implementation by the smart contract.

Testing of the contract after coding and getting a security audit are highly recommended.

Step 4: Connect the AI Model

The next phase involves integrating the artificial intelligence model with blockchain tools.

A large language model can be used to understand information and determine which particular tool has to be used. The agent framework can offer the tools required for the analysis of blockchain information, balance check, contract queries, and transaction generation.

Step 5: Give the Agent a Wallet

The agent must create a blockchain identity to work with the smart contract.

This can be done by using a special wallet or a system of private key management. Nonetheless, the private keys must never be stored within the prompt, source code, or any other public location.

When working on production systems, utilize secure key management infrastructure and restrict wallet permissions where possible.

Least privilege is a good concept to implement: if the agent requires permission to do one particular thing for which it is paid, then there is no need to grant it access to the entire treasury.

Step 6: Add On-Chain Data and External Tools

AI agents become more useful in case they have access to reliable information.

In terms of application cases, an AI agent may need either blockchain RPC providers, contract APIs, price feeds, transaction history, decentralized storage, or other data sources.

However, information provided by the AI itself cannot be regarded as reliable in any way. All important decisions must be made using only reliable sources of information and deterministic logic of smart contracts wherever it is possible.

For example, the AI agent can suggest some actions to take based on the market data, and the smart contract can verify whether the transaction falls under some limits.

Step 7: Add Human Approval and Safety Controls

Autonomous execution should be introduced carefully.

A safer architecture can require human approval for high-value or unusual transactions while allowing low-risk operations to happen automatically.

Additional safeguards can include:

• Spending limits
• Allowlisted contract addresses
• Rate limits
• Transaction simulation
• Emergency pause functions
• Multi-signature approval
• Monitoring and alerts

These controls reduce the consequences of incorrect AI decisions, compromised wallets, malicious inputs, and unexpected smart contract behavior.

Step 8: Test and Deploy

Do all the testing of each component before the agent goes live.

Begin with unit testing the smart contract and then do integration testing of the whole agent process on a test network. Test successful and failed transactions, unexpected input, congested network, incorrect output of AI, and lack of balance.

Observe transactions on the live network and have some procedure to shut down the agent in case of unexpected behavior.

It’s not enough just to create an agent that can perform transactions. The main task is to make the actions of this agent predictable, limited, observable, and reversible.

Why building an on-chain AI agent is more than connecting an AI model to a crypto wallet

Creating an AI agent for on-chain operations is not only about tying together an AI system and crypto wallet. The optimal architecture divides roles between the AI and blockchain.

The former may analyze available data and decide what course of action should be taken, whereas smart contracts make sure that what should be done by blockchain is enforced through the rule system. Having access rights set for wallets, reliable data sources, transaction limits, testing, and human involvement, programmers are able to build agents that will interact with blockchain apps without letting the AI have full control of assets.

Smart contracts can play an essential role in creating transparency and restrictions for AI agent actions.

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