The real test of an AI agent isn’t how smart it sounds, but what happens when it makes a costly mistake.

Imagine asking an agent to pay for a research API. It finds a service, makes the payment, and gets the data. But what if it picks the wrong endpoint or keeps spending on repeated requests?

This is where the rules around spending matter. Kite Passport lets users approve a session with a passkey, setting a total budget, a per-transaction limit, and an expiry time. The agent can pay for supported services within those limits, while users can review payment activity.

That helps control how much money can be spent, but it doesn’t guarantee the agent will make good decisions. It could still trust outdated information or choose a service that doesn’t meet the need.

I think that distinction matters. We shouldn’t measure an agent only by how much work it can do without us. We should also ask whether its mistakes are contained and whether we can understand what happened.

Giving an agent a small, task-specific budget seems more sensible than trusting it with broad access from day one.

What would you limit first: its budget, its access, or the decisions it can make?

#KiteBBW $KITE @KITE AI