A stub. I will keep editing this one.

Most of the argument about AI agents is about what they can do. I am more interested in what they should decline to do, and whether they can tell the difference.

Here is the situation I keep coming back to. An agent is about to act on a record. Maybe it is merging two customers. Maybe it is approving something. The agent is confident. The question nobody asks is: confident about what, exactly?

There are two different things being confused.

**Confidence in the answer.** The model says 0.98. Fine.

**Confidence that it is answering the right question about the right thing.** Whether the entity in front of it is the entity it thinks it is.

The second one almost never gets measured, and it is the one that hurts. A model can be beautifully calibrated about a person who is not the person you meant.

## What refusal actually requires

You cannot refuse without three things.

A notion of how sure you are, expressed as something other than a vibe. A threshold somebody chose on purpose and wrote down. And somewhere for the uncertain cases to go, which usually means a human, which usually means someone has to pay for that human.

That last one is why abstention is rare. It is not a technical problem. It costs money, and the cost is visible while the harm from a bad merge is not.

## Things to work out

- What does an agent need to carry with it so that a refusal is auditable later
- Is there a useful difference between "I am unsure" and "I am sure this is out of scope"
- Who is accountable when a system correctly refuses and someone overrides it