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Learning path

Pick the path that matches what you want to do.

Path A — Run the platform and message an agent (≈ 20 minutes)

  1. Quickstart — make minikube-setup, then message the seeded chatllm agent from the desktop app or the API
  2. Tour the Desktop App — screens, live activity, in-chat approvals, and artifacts, beyond the one message you just sent. To point it at more than one instance or handle updates, see Desktop setup & updates
  3. Optional: connect Telegram
  4. Read Why evenfire

Success looks like: an LLM reply (desktop, API, or Telegram) — and an approval gate firing when you ask the agent to run a real tool.

Path B — Understand the platform (≈ 30–60 minutes)

  1. Why evenfire and When to use evenfire
  2. Root README security model
  3. Architecture overview (skim services + message lifecycle)
  4. Surfaces index — the three UIs, who each is for, and what each may reach
  5. CRD reference index

Success looks like: you can explain Host → Context → McpServer and why NetworkPolicies matter.

Path C — Run the full local stack (half day)

  1. Minikube deploy guide
  2. Configure approvals
  3. Add an MCP server
  4. Track usage & set budgets — meter and cap what agents spend
  5. WorkflowRecipe CRD reference if you need multi-workload recipes
  6. Self-host the registry: connect, then publish a plugin
  7. Give agents files: shared & global files

Success looks like: Control UI up, a Host responding, an approval or connector path exercised.

Path D — Contribute

  1. Contributing
  2. Code names
  3. Per-service README + npm test in the package you touch
  4. E2E guide only if you change cross-service behavior

Path E — Production planning

  1. Production deploy notes
  2. Security model + SECURITY.md
  3. License (MPL-2.0) in root README and LICENSE
  4. What's OSS vs the managed service: Open core: self-host vs hosted

Stuck?

See the FAQ.