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Sponsored gas can simplify on-chain actions initiated by an AI agent, but it also transfers execution risk to the sponsor. This technical runbook specifies measurable budget, validation and reconciliation controls without presenting proposed ERC interfaces as settled guarantees.
Gas sponsorship changes who bears the downside
An AI agent that purchases an on-chain service may use a smart account with ERC-4337 rather than requiring a user to handle every gas payment. When an application offers sponsored gas, the paymaster becomes the party exposed to execution cost and malicious retries. A user-visible label saying “gasless” does not mean the network transaction is costless. Someone has funded the paymaster, set a sponsorship rule and accepted potential failure expense.
The ERC-4337 specification describes UserOperations, bundlers, validation and paymaster deposits at the EntryPoint. A sponsor therefore needs an accounting model distinct from token transfer balances. Track the operation hash, chain ID, sender, service policy, maximum authorized cost, actual gas charged and resolution state. Do not use an AI agent’s natural-language promise as the authorization record; rely on structured transaction boundaries.
Distinguish a quote, an authorization and a final charge
The proposed ERC-7677 Paymaster Web Service Capability, created in April 2024 and still identified as a proposal, defines interfaces for obtaining preliminary sponsor data and final paymaster data. The distinction between stub data and finalized data matters because estimates may change after a wallet assembles a UserOperation. Wallets may also choose another paymaster, so an application should not infer the ultimate sponsor merely because it supplied a service URL.
A clean ledger gives each sponsorship decision an immutable policy ID and a short expiration. A preflight quote is provisional; a signed authorization reserves a capped budget; a confirmed execution settles the actual cost. If a quote expires or a transaction fails to enter a block, release the reservation under documented conditions. Reconcile the ledger with on-chain events rather than only webhook acknowledgements from a middleware provider.
Build budget limits that survive agent retries
A naive daily limit counts successful transactions only. An autonomous agent can consume sponsor resources with repeated reverts, invalid data or multiple small operations. Define layered controls: a per-user daily cap, per-task cap, per-chain cap, rate limit, allowed contract set and a global emergency cutoff. The limits should be enforced before issuing paymaster authorization, not after costs have already accumulated.
For example, suppose an experimental sponsor allocates 0.02 ETH per day to one workflow. Four attempted operations each reserve 0.006 ETH. The fourth should be rejected if the previous three reservations are still active because a fourth would exceed the 0.02 ceiling. This is a hypothetical arithmetic scenario, not an observed gas price or market recommendation. It illustrates why outstanding reservations belong in the budget denominator.
Treat validation and execution as separate risk zones
ERC-4337 requires a bundler to simulate validation, and the paymaster must verify willingness to sponsor a UserOperation. The project’s paymaster security documentation also discusses griefing, deterministic validation and post-operation responsibilities. Nonetheless simulation is not an economic guarantee: execution environment changes, legitimate reverts and policy implementation bugs still affect realized cost. Include the EntryPoint version, gas limits and any postOp allowance in the authorization record.
Maintain a replayable test suite for a valid action, forbidden target, oversized gas request, stale quote, replayed nonce, malicious calldata, failed downstream contract and exhausted sponsor deposit. Verify that denial cases do not leak secret signing material or grant the AI agent fallback unlimited sponsorship. A production review should also distinguish the paymaster’s deposited ETH from any separate staking requirement, rather than combining them into a misleading available-balance figure.
Keep paymaster keys away from client and model
ERC-7677’s security discussion notes that service URLs may contain API keys and recommends a backend proxy where appropriate. Never embed a privileged sponsorship API secret in mobile code, an AI prompt or a publicly logged tool response. Let the backend validate policy, sign or request paymaster data, and return only the parameters the wallet needs. The agent should express proposed intent but not override spending limits through persuasive text.
Bind authorization to chain, EntryPoint version, wallet, operation hash or sufficiently precise operation fields, expiry and sponsor policy. Enforce separation of duties for budget increases; alert on unusual rejection patterns, repeatedly changing counterparties and rising failure expense. The ability to terminate sponsorship should work without waiting for the AI model to cooperate. This is the practical difference between an agent that suggests an action and a system that authorizes a payment.
Measure unit economics and incident response
For a creator or social application subsidizing microtransactions, report sponsorship per eligible user action, not simply total gas spent. A useful breakdown contains approved requests, included UserOperations, successful business outcomes, execution failures, average sponsor cost per valid outcome and reserve utilization. Counterfactual user retention benefits should be described as hypotheses unless measured through a properly designed experiment.
Prepare a runbook for unexpected drain: disable new approvals, revoke exposed service credentials, inspect recent policies, reconcile on-chain costs and identify whether the loss came from validation, repeated legitimate actions or execution outcomes. Avoid claiming that on-chain immutability solves off-chain billing disputes. The release criterion should be a fully reproducible sponsor ledger with bounded loss, explicit approvals and reversible configuration changes, rather than a demo in which one operation happens to succeed.
