Build a practical mental model of large language models - what they actually do, where they break, and how to choose one for infrastructure tasks. No hype, just the mechanics you need to use LLMs confidently with Meshery.
Learn how to write prompts that produce reliable, parseable output from an LLM when your inputs are real infrastructure state and your outputs drive real changes to a Kubernetes cluster.
Understand what a coding agent is, how the agentic loop works, and how to apply agents safely to infrastructure operations with appropriate human oversight.
Learn how to ground infrastructure agents in current, specific state rather than stale training data by building retrieval pipelines over cluster state, Meshery data, and operational knowledge bases.