platform engineering

From notebook to production, this Bash-first Linux guide builds a minimal AI platform: containerized FastAPI inference (Podman/Docker), reproducible training artifacts, MLflow experiment tracking, GitHub Actions CI/CD to ship images, and Prometheus/Grafana observability, improving speed, reproducibility, cost control, compliance, and creating a repeatable develop-ship-run loop.

Guide for platform engineers/SREs to use LLMs as Bash tools that read diffs, logs, and Kubernetes manifests so humans decide faster. Provides an OpenAI-compatible ai() helper and three scripts: summarize PR risk, triage logs to strict JSON, and lint live K8s resources. Includes setup with curl/jq/git, CI guardrails (determinism, clipping, redaction), and self-hosted endpoints for privacy and cost control.