How Often Do You Review Your AI Output? Code vs. Communications

How often do you review your AI output in CODE vs. COMMUNICATIONS?

I'm curious, because I suspect most of us are much more rigorous with one than the other. Recently, I've been triggered by the sheer volume of posts, memos, and client emails that are clearly unedited before sending. I legitimately hope we aren't maintaining that same careless ratio in production code.

People seem to be using prompt packs they find online with a bizarre mindset: "Some smart person wrote this prompt, and the smartest machine ever made answered it, so it's fine to copy, paste, and call it done."

Surprise: an LLM probably hallucinated the prompt pack you paid $49 to download, too.

Cognitive Surrender vs. Real Expertise

Hot take: AI-generated content scraped from your "second brain" is not expertise. It isn't thought leadership, it isn't AEO optimization, and it isn't good business practice. It's just cheap marketing filler.

The actual value of experience is knowing when something doesn't make sense, identifying what's missing, and knowing when the output needs to be challenged.

I used to teach a university engineering course dedicated solely to engineering judgment and professional ethics. It breaks my heart when people—especially senior leaders who should know better—willingly cede away their intuition in favor of convenience. A colleague recently called it "cognitive surrender," and that phrase hits the nail on the head.

We genuinely need the accumulated expertise that lets an experienced builder look at an output, pause, and say: "Wait. That doesn't smell right."

Judgment Is the Only True Differentiator Left

AI doesn't make human judgment less valuable; it makes judgment the only true differentiator you have left.

The more capable generative models become, the more critical it is that someone with battle-tested experience stands between the model's raw output and the real world. That applies whether you're reviewing a distributed Cloud Run microservice, structuring a residential transaction pipeline, or sending an executive advisory note.

If you never review an AI output before passing it along to your clients or colleagues, you aren't exposing a limitation in AI. You're exposing a flaw in your own work ethic. And the next time I see unedited AI slop in my inbox, I'll almost certainly judge you—not the model.