Automation engineer moving into DevOps?

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Background: about 14 years in the industry (CS Degree), started in manual QA, roughly 6 years in automation (Node/Playwright, GitLab CI). I'm now migrating pipelines from 2 other devops tooling (Jenkins and TeamCity) to GitLab CI/CD, deploying with Helm to kOps-managed clusters on AWS, mostly .NET apps. I'm trying to turn that into a real platform/DevOps role. Most of what i've done recently in the past year has been AWS + Terraform but im pretty used to Gitlab and it's CI/CD via the Automation stuff. This post sorta edges between job stuff and actual "learning" so I wasn't sure where it belongs. My problem is retention more than motivation: * Most of our Dockerfiles and manifests already exist, and I lean on AI for drafts, so I review and edit much more than I write. The concepts stick, but exact syntax fades. * I use Terraform, but not daily. I took a practice quiz aimed at state, import, and drift and got 3 out of 6. * Linux is my weakest layer. We're mostly a Windows shop, so I rarely live in a terminal on Linux boxes. * I've fallen into tutorial hell before, so I'm trying to learn by building things. What I'm doing about it: a small homelab (Proxmox, a few LXC services, k3s next), a KodeKloud subscription, and my employer covers certs. Current cert plan: 1. KCNA 2. Terraform Associate (004) 3. An AWS Associate (Solutions Architect or CloudOps) 4. CKA, once I have real Kubernetes hands-on I'm skipping the Docker cert because it looks Swarm-heavy and I don't use Swarm. Questions for people further along: 1. Does that order make sense, or would you change it? 2. How do you keep skills current in areas your job doesn't exercise day to day? Cheat sheets, a homelab, something else? 3. If you made the QA/automation-to-DevOps jump, what did hiring managers actually weigh: certs, homelab, or real migration work? 4. How do you keep AI-drafted YAML and Dockerfiles from turning into a crutch? 5. Curious if this happens to anyone else? specifically with like Terraf

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