It's not uncommon for Aampe customers to ask how to audit a single agent’s decision. It’s a fair question, but I'm inclined to counter it with another question:
How do you audit a single *human’s* decision?
You can ask someone why they did something, and they’ll almost always give you an answer. It’ll sound reasonable. It’ll feel complete. And it’ll almost certainly be — at least partially — wrong. Not intentionally. Just...human. We act on habits, hunches, patterns we don’t even realize we’ve learned. Most of the reasoning happens under the surface.
Agents are more like people in that way than they are like traditional software. Technically, we *can* trace all the data that shaped an agent’s behavior. Every user event, every reward signal, every update to the policy distribution — it’s all there. But that data gets sampled, aggregated, and transformed constantly. By the time a message gets sent, the decision has passed through too many layers to cleanly unpack. And even when you *can* unpack it, the answer often isn’t useful. It’s a just-so story, not a lever you can pull.
That doesn’t mean you can’t question your agents. You should. But the useful questions usually aren’t “Why did the agent send this message to this user yesterday morning?” They’re more like:
“Why aren’t agents messaging around use case A as often as I would like?”
“Why are they ignoring product category B when that’s what we want to push?”
These questions are about system behavior, not individual moves.
And more importantly, they point to actions you can take: update the content library, re-balance priorities, clarify the business objectives.
If you want your agents to act like teammates, treat them like teammates. Don’t expect perfect introspection. Give them more clarity about what you need from them.
