Organize AI Chaos With Platform Engineering
summary
Platform engineering centralizes LLM metadata (owner, infra region, token budget, status) and exposes opinionated self‑service for RAG stacks by modeling prompts, vector DBs and pipelines as Kubernetes resources. Demo uses Kubernetes CRDs, GitOps with Argo CD and GitHub Actions, an internal portal (Port) and an MCP prompt server to register templates; creating a prompt YAML opens a PR, Argo syncs it and the prompt becomes immediately available — the end‑to‑end flow works.
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chapters (6)
- 0:00Introduction
- 2:10What is platform engineering
- 8:52AI’s impact on cognitive load
- 15:16Solving AI chaos with platform engineering
- 19:56Live demo: prompt management with Kubernetes
- 25:35Conclusion & Q&A
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