With so many different syntaxes and configs in our daily stack—CI/CD pipelines (GitHub Actions, GitLab), Terraform modules, Kubernetes manifests, Dockerfiles, Ansible playbooks, and Bash scripts—nobody can memorize every block and flag from scratch.
My current workflow is to use AI or existing templates to generate the initial boilerplate for Terraform resources, pipeline YAML, or K8s manifests, and then manually write, wire up, and audit the core architecture, state management, IAM/permissions, networking, and security logic.
For those working in production environments (and those running technical interviews):
1. In your day-to-day work, what parts of the stack do you still write completely by hand vs prompting an LLM or pulling from docs?
2. Where has AI actually helped you across Terraform, CI/CD, and K8s, and where does it consistently break things?
3. What is the realistic expectation in interviews right now regarding writing configs from memory vs understanding the underlying systems and debugging?