AI Agent Spending Limits

Giving an AI agent the ability to spend money is powerful — but without guardrails, it's dangerous. An agent stuck in a retry loop could drain hundreds of dollars in minutes. A hallucinating agent could authorize payments to the wrong service. A compromised API key could lead to unauthorized spending. Spending limits are the safety net that makes autonomous agent payments practical for production use. Locus provides a three-layer policy engine that checks every single transaction before it executes, giving you fine-grained control over how much your agents can spend, when, and on what.

Beyond aggregate budgets, Locus enforces rules at the individual transaction level. Every API call or payment is checked before execution.

• •Max per-transaction amount — Set the maximum USDC an agent can spend in a single API call or payment. Prevents accidentally calling an expensive endpoint with a large payload.
• •Approval thresholds — Transactions above a certain amount can require human approval before executing. For example, auto-approve anything under $5 but flag purchases over $5 for review.
• •Rate limiting — Limit the number of transactions per minute or per hour to prevent runaway loops from draining the wallet.
• •Endpoint allowlists — Restrict which APIs or services the agent is permitted to call. An agent assigned to research doesn't need access to image generation endpoints.

A customer running an autonomous research agent sets a $20/day budget with a $2 per-transaction limit. The agent calls Tavily for web search, Anthropic's Claude for summarization, and CoinGecko for market data at each tool's published price. It operates freely within those bounds. If it encounters a retry loop, the per-transaction limit prevents any single call from being expensive, and the daily budget caps total exposure. The human operator reviews the audit trail the next morning and adjusts policies as needed — without ever having been woken up at 3 AM for an approval.