You can use an AI coding agent (GitHub Copilot in VS Code/Codespaces, Claude Code, OpenAI Codex, Cursor
and others) as a lab partner. The repository ships guidance so your agent understands this
environment:
File
Read by
Contains
AGENTS.md
Copilot, Codex, Cursor, Gemini CLI, most agents
How KID is wired, safety rules, where things live, how to validate changes
CLAUDE.md
Claude Code
Imports AGENTS.md
.agents/skills/
Agents that support Agent Skills (also linked as .claude/skills and .github/skills)
Step-by-step procedures, loaded only when relevant
Run the agent inside the dev container (the default in Codespaces and VS Code Dev Containers).
That's where kubectl, hubble and friends can reach the cluster.
The guidance tells the agent to teach rather than just solve: it gives hints for the "Check
your understanding" questions unless you ask for the answer. Ask it to explain its commands.
The agent is told not to weaken guardrails (network policies, Kyverno, quotas) to make
something work, and to ask before destructive actions. If a lab is about breaking something,
say so.
Changes under gitops/ only reach the cluster after you commit and push to your fork (then
tre sync). The agent should tell you which changes are GitOps and which are direct kubectl.
Treat agent output like a colleague's: read the diff before you commit it.