Been interviewing DevOps candidates for six months. Out of maybe 40 people, three could do basic Linux admin without looking like a deer in headlights. The rest had AI-generated resumes and couldn't grep their way out of a paper bag.

Here's how we got here.

Stage 1: You Write the Tests

You're using ChatGPT or Copilot to crank out code. Fine. But you write your own tests. You understand what the code is supposed to do because you're defining the contract. You're still an engineer.

This stage is tolerable. It's autocomplete with delusions of grandeur. The AI suggests, you verify, you ship. You could delete the AI tomorrow and still function.

Stage 2: The AI Writes the Tests Too

Congratulations, you've entered the hallucination loop.

Now the AI writes both the implementation and the tests. The tests pass because the AI made them pass. The code might be subtly broken, the tests might be validating the wrong behavior, but hey — green checkmarks.

Here's the real mindfuck: when you ask the AI to "fix the failing test," you have no idea what it actually did. Did it fix the buggy code? Or did it just rewrite the test to expect the buggy behavior?

You'll never know. Because you didn't write either one. The AI could be changing assertEquals(5, result) to assertEquals(4, result) because the code is wrong and it's easier to adjust the assertion than fix the logic. And you'd never notice.

You're no longer verifying anything. You're just watching two instances of the same LLM agree with each other and calling it validation. This is the software equivalent of asking your drunk friend if you're drunk.

At this point you don't understand the code or the tests. You're a deploy button with a pulse.

Stage 3: You Stop Reading Code Entirely

Peak vibe coding.

You paste requirements into Claude, it barfs out 300 lines, the tests pass (tests you didn't write, testing behavior you didn't define), the build is green, you merge.

Your entire quality bar: it compiles and the CI doesn't fail.

You have no idea what the code does. You cannot debug it. You cannot explain it in an interview. You're just sitting there refreshing the GitHub Actions page like it's a slot machine.

The Interview

This is where I meet you.

"Can you explain how this recursive function works?"
You stare at it. It's in your own repo. You wrote it. Apparently.

"Can you SSH into this box and tell me what's eating CPU?"
You type top. You stare at the output. You have no idea what you're looking at.

"Write a bash script that processes these logs."
You open ChatGPT.

You've been vibe coding for 18 months and now you're in my conference room unable to explain what a file descriptor is.

Look

I'm not some cranky Luddite. I use AI tools every day. They're great for boilerplate, for suggesting patterns I forgot, for handling the boring parts. But if you can't read the code, you're not an engineer. You're a build system operator.

When you hit Stage 3, you can't mentor anyone, you can't debug production, you can't reason about edge cases, and you sure as hell can't explain your own codebase during an interview.

If you're in Stage 2 or 3: stop. Read the damn code. Write your own tests. Understand what's happening. The AI is a tool, not a substitute for your brain.

Or keep going, I guess. I need people to interview so I can tell my VP we couldn't find qualified candidates this quarter either.