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Trust & Constraints

How much financial autonomy should you give an AI agent? The answer is simpler than most people think.

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The Pocket Money Philosophy

Think of funding an agent wallet like giving pocket money. You put in what’s appropriate for the task — not your entire portfolio. The agent operates autonomously within that scope. If something goes wrong, you lose the pocket money, not everything. This is deliberately simpler than:

• Complex policy engines that require extensive configuration before your agent can do anything
• Role-based permission systems that add integration overhead and maintenance burden
• Multi-approval workflows that defeat the purpose of autonomous operation

The constraint is the balance. If you fund a wallet with $50, the worst case is losing$50. No policy engine needed. No configuration. The constraint is immediate, obvious, and enforced by the blockchain itself.

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How to Think About Funding

Start small. Always. Fund what you need for the immediate task, see how the agent performs, and increase as you gain confidence. Match funding to the task. A research agent that buys API access needs $10–50. A trading agent running a strategy might need$500. An enterprise payment agent might need more. Let the task dictate the amount. Refill rather than pre-fund. It’s better to add $100 five times than to deposit$500 upfront. Each refill is a checkpoint — a moment to review what the agent did with the previous funds.

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Setting Constraints

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Balance Is the Primary Constraint

The amount in the wallet is the most powerful constraint you have. It’s:

• Enforced by the blockchain — the agent literally cannot spend more than what’s in the wallet
• Immediately effective — no configuration, no policy language, no deployment
• Transparent — you can check the balance at any time via any block explorer
• Universal — works the same regardless of which interface the agent uses

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Progressive Trust

1. Test phase — Fund with test tokens on a testnet. Let the agent experiment freely. Cost: zero.
2. Small real funds — Fund with $10–50 on mainnet. Verify the agent does what you expect.
3. Working amount — Once you trust the behavior, fund what the use case actually needs.
4. Scale up — Increase funding as the agent proves itself over time.

Each step is a conscious decision. There’s no automation that escalates trust — you decide when to increase the balance.

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Trust Patterns by Use Case

Most entries in this table are EOA — because most agent use cases work perfectly with just sensible balance management.

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When Simple Constraints Aren’t Enough

The pocket money approach works for the vast majority of use cases. But some scenarios call for more: You need batch transactions or gas abstraction → Smart Account adds programmable on-chain logic, session keys, and gas sponsorship. You need on-chain spending limits → Delegated wallet adds granular spending controls enforced by the smart contract itself. You need multi-party approval → Delegated wallets support approval workflows for high-value operations. The key principle: don’t over-engineer trust controls before you need them. Start with sensible funding. Upgrade only when the use case genuinely demands it.

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Common Mistakes

Over-funding early. Developers deposit large amounts “to avoid having to refill.” This removes the natural safety net. Fund small, refill often. Over-engineering controls. Building complex permission systems before you’ve validated the agent’s behavior. Start with pocket money. Add controls when you have real data on what the agent does. Under-monitoring. The pocket money approach doesn’t mean “fund and forget.” Check your wallet’s on-chain activity periodically. Block explorers make this trivial. Treating all agents the same. A research agent and a trading agent have very different risk profiles. Fund each according to its purpose, not with a blanket amount.