Your AI agent completed the task. But can you explain how

Something I've been thinking about while working on AI agents:

We spend a lot of time making agents complete tasks, but less time thinking about how to reconstruct what happened during execution.

Imagine an agent that calls five APIs, retrieves context, retries a failed operation, and produces the correct answer.

Now imagine something goes wrong.

Can you see which tool failed? What context it used? Why it retried? Whether approval was required?

And can you replay that execution safely without repeating real-world actions?

This is an underrated challenge of moving AI agents from demos to real products.

At Nuroen, we're focused on governed agent execution, where traceability and debugging matter.

Curious how other indie builders handle this.

Are you building execution tracing from day one, or adding it when debugging becomes painful?