Let’s be trustworthy.
You and your crew have in all probability used ChatGPT to put in writing a Terraform script, draft a Helm chart, and even debug a failing CI job.
No judgment — we’ve all performed it.
However right here’s the scary half no person talks about:
These LLMs have gotten a part of your DevOps workflow…
With none evaluate. With out validation. And infrequently, with out anybody realizing.
And that’s not simply harmful — that’s a ticking time bomb.
While you ask ChatGPT or Copilot to “write a Dockerfile for a Node.js app”, it provides you a superbly structured reply in seconds.
However do you actually know what it’s doing?
- Are the variations pinned correctly?
- Is it including vulnerabilities like outdated base pictures?
- Does the generated YAML file expose ports publicly?
- Did it reuse another person’s insecure GitHub snippet?
Let’s be actual — most of us copy, tweak barely, and push.
And now that AI-generated code is working in manufacturing.
