Audit Your AI's Work. Every Time.

My four most-used prompts when working with AI agents have nothing to do with being clever. They’re all some version of: “audit yourself.”

I use Claude Code to build and maintain the skills and processes that run my company. Hundreds of interconnected files. Rules that reference other rules. Defaults that cascade across systems.

When I ask it to make a change, like updating a deck theme or rewriting a workflow, it does it. Fast. Confidently. Tells me it’s done.

I never take that at face value.

Here’s the loop I run every single time:

“Audit all the changes you just made.”

“Make sure you’ve applied them everywhere.”

“Check for any conflicting or contradictory instructions.”

“Go back and confirm you’ve actually converted everything I requested.”

That last one is the kill shot. You’d be surprised how often the AI says “done” and then, when pressed, finds three more places it missed. A rule that contradicts the new one. A section it updated in one file but forgot the four other files that reference the same thing. An old default it left in place because it didn’t think to look.

AI is lazy in the same way people are lazy. It does 80%, declares victory, and moves on. Not maliciously. It just optimizes for completion over thoroughness.

The fix is simple. Don’t trust, verify.

I learned how concrete that has to be when I caught an AI rubber-stamping a quality check instead of actually inspecting the work.

I think about it the same way you’d think about checking a junior employee’s first attempt at something important. The work might be 90% right. But the 10% it missed is where you get burned.

The people getting the most out of AI right now aren’t the ones writing elaborate system prompts. They’re the ones who refuse to accept “done” at face value. They run audit loops. They push back. They make the AI prove its own work.

30 seconds of follow-up prompts saves 30 minutes of debugging later.