AI coding agents are remarkably good at getting from “here’s what I want” to “here’s a working implementation.”

They are also remarkably good at being satisfied with what they just built.

That second trait is a problem.

One of the highest-leverage habits I’ve picked up when working with coding agents is surprisingly simple:

After the agent finishes a meaningful piece of work, ask it to perform an adversarial review of its own implementation.