AI Replaced 80% of My Repetitive DevOps Tasks. That Was the Good Part.

Most engineers talk about AI. I wired it into production and let it handle the boring parts. GitHub Copilot runs in my daily Terraform workflows. Azure OpenAI is connected to production logs - when an incident fires, it groups related alerts and drafts a summary before I've finished reading the first one. Dashboards surface issues before humans catch them. RAG pipelines are already in prototyping for intelligent incident grouping, with vector databases sketched out for spotting trends across months of observability data. Not demos. Production systems. Copilot isn't magic. It suggests wrong provider versions, hallucinates resource attributes, confidently recommends things that don't exist. I treat it like a fast junior - high output, needs review. But the speed gain is real enough that going back doesn't feel like an option. The Azure OpenAI piece is where things got genuinely interesting: that summaries-before-you've-read-the-first-alert workflow changed how I handle on-call more than any tooling change in years. AI in DevOps right now feels exactly like DevOps felt years ago - rough, messy, half the tools broken, but the other half changing how you work. The engineers building…