Can AI agents accidentally hide broken processes?

Here’s a failure mode I don’t see discussed much.

Imagine an operations agent notices that every morning, 30 orders arrive with incomplete shipping information.

So it:

Great automation.

A month later, the agent has fixed 900 orders.

Everyone thinks the workflow is working.

But the real problem is still there:

Why are 30 broken orders being created every day?

Before AI, someone doing this manually would probably complain after the third day.

An agent might quietly keep fixing it forever.

That creates an interesting problem.

AI agents can reduce operational pain so effectively that they also remove the signal that something upstream is broken.

The better the agent gets at handling exceptions, the easier it becomes to normalize those exceptions.

Maybe production agents shouldn't just report what they completed.

They should also surface patterns like:

“I’ve had to fix the same underlying problem 427 times this month.”

At some point, automation should stop being the solution and start pointing at the process that needs fixing.

Curious how others think about this.

Could highly capable agents actually make bad processes harder to notice?

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