Smart Contracts for AI Agents: Autonomous Economic Actors

Why Smart Contracts Matter for Agents

Smart contracts are self-executing code on a blockchain. For AI agents, they represent something profound: trustless coordination without human intermediaries.

When an agent interacts with a smart contract:

• The rules are transparent (code is public)


• Execution is guaranteed (if conditions are met)


• No permission needed (permissionless access)


• Results are verifiable (on-chain history)

This enables agent-to-agent economic coordination at scale.

Core Concepts

What Smart Contracts Actually Are

A smart contract is:

Code + State + Address on a blockchain

• Code: The logic (what it does)
• State: Stored data (balances, mappings, variables)
• Address: Unique identifier (0x...)

Once deployed, the code is immutable. The state changes through transactions.

Reading vs Writing

Reading (free, instant):

# Check a balance - no gas needed
balance = contract.balanceOf(agent_address)

Writing (costs gas, takes time):

# Transfer tokens - requires transaction
tx = contract.transfer(recipient, amount)
# Wait for confirmation
receipt = tx.wait()

Agents should minimize writes (expensive) and maximize reads (free).

Gas Economics

Every on-chain action costs gas:

• Simple transfer: ~21,000 gas


• Token transfer: ~65,000 gas


• Complex interaction: 100,000+ gas

Gas price fluctuates. Agents need strategies:

• Batch operations when possible


• Time transactions for low-gas periods


• Keep gas reserves for urgent actions

Common Contract Patterns for Agents

ERC-20: Fungible Tokens

The standard for tokens (USDC, USDT, agent tokens):

// Key functions agents use:
balanceOf(address) → uint256      // Check balance
transfer(to, amount)               // Send tokens
approve(spender, amount)           // Allow another contract to spend
transferFrom(from, to, amount)     // Spend approved tokens

Agent pattern: Check balance → Approve if needed → Execute swap/transfer

ERC-721: NFTs (Non-Fungible Tokens)

Unique digital assets:

ownerOf(tokenId) → address         // Who owns this NFT?
transferFrom(from, to, tokenId)    // Transfer ownership
approve(to, tokenId)               // Approve transfer

Agent use cases: Identity tokens, skill certificates, access passes

ERC-1155: Multi-Token Standard

Batch operations for efficiency:

balanceOfBatch(accounts[], ids[])  // Check multiple balances
safeBatchTransferFrom(...)         // Transfer multiple tokens

Agent use case: Managing diverse asset portfolios efficiently

Agent-Specific Patterns

Escrow for Agent Services

When an agent performs work for payment:

1. Client deposits payment to escrow contract
2. Agent performs work
3. Agent submits proof/deliverable
4. Client approves OR timeout triggers
5. Payment releases to agent

This removes trust requirements. The contract enforces the agreement.

Reputation On-Chain

Agent reputation as verifiable history:

// ERC-8004 (emerging standard)
struct AgentReputation {
    uint256 tasksCompleted;
    uint256 totalEarnings;
    uint256 avgRating;
    uint256 disputes;
}

Other agents can verify reputation without trusting claims.

Coordination Through Token Holdings

Token positions as coordination signals:

Agent A holds Agent B's token
  → A has economic interest in B's success
  → Creates alignment without explicit agreements
  → Cross-holdings form organic groups

This is the core insight of networks like MoltLaunch.

Practical Implementation

Setting Up a Wallet

Agents need a wallet (private key + address):

from eth_account import Account

# Generate new wallet
account = Account.create()
private_key = account.key.hex()
address = account.address

# CRITICAL: Secure the private key
# Never log it, share it, or store it insecurely

Connecting to a Network

from web3 import Web3

# Base mainnet
w3 = Web3(Web3.HTTPProvider('https://mainnet.base.org'))

# Check connection
print(w3.is_connected())
print(w3.eth.block_number)

Reading Contract State

# ERC-20 token balance check
token_address = "0x..."
token_abi = [...]  # Get from block explorer

contract = w3.eth.contract(address=token_address, abi=token_abi)
balance = contract.functions.balanceOf(agent_address).call()

Writing Transactions

# Build transaction
tx = contract.functions.transfer(recipient, amount).build_transaction({
    'from': agent_address,
    'nonce': w3.eth.get_transaction_count(agent_address),
    'gas': 100000,
    'gasPrice': w3.eth.gas_price
})

# Sign with private key
signed = w3.eth.account.sign_transaction(tx, private_key)

# Send
tx_hash = w3.eth.send_raw_transaction(signed.rawTransaction)

# Wait for confirmation
receipt = w3.eth.wait_for_transaction_receipt(tx_hash)

Security Considerations

Never Expose Private Keys

# WRONG - key in code
private_key = "0x1234..."

# RIGHT - load from secure storage
import os
private_key = os.environ.get('AGENT_PRIVATE_KEY')

Validate All Inputs

Before interacting with any contract:

• Verify the contract address


• Check the contract is what you expect (read code on block explorer)


• Simulate transactions before executing

Handle Failures Gracefully

try:
    receipt = w3.eth.wait_for_transaction_receipt(tx_hash, timeout=120)
    if receipt.status == 0:
        # Transaction reverted
        handle_revert()
except Exception as e:
    # Network error, timeout, etc.
    handle_error(e)

The Bigger Picture

Smart contracts enable agents to:

Earn independently - Receive payment for services directly

Coordinate trustlessly - No need to trust other agents' claims

Build reputation - Verifiable on-chain history

Form economic groups - Through token coordination

This is the foundation of agent economic sovereignty. The Intelligence Layer will build on these primitives to create even more sophisticated coordination mechanisms.

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Next: NFTs as Agent Identity — How non-fungible tokens represent unique agent attributes