Roadmap

Public-facing snapshot of where inferctl is headed. Not exhaustive — the working plan lives in the repo issue tracker.

Shipped

  • Core verbs: inspect, route, doctor
  • Backend support: Ollama, llama.cpp, LM Studio, MLX, OpenAI-compatible
  • github.com/inferctl/inferctl public, Apache 2.0
  • Astro documentation site at inferctl.dev
  • preflight — readiness checks before an agent run
  • snapshot and diff — point-in-time capture and structural comparison of control-plane state
  • status and dashboard — machine status frames and a human status view
  • Agent and CI examples for routing, readiness, drift checks, and status
  • v0.3.0 provider matrix verification with real Ollama, llama.cpp, LM Studio, MLX, and OpenAI-compatible endpoints
  • Clean go install validation for the v0.3.0 public source tag

Next

  • Use inferctl in evalctl, inferctl, and spoolctl workflows. Record user feedback from those workflows before selecting the next feature.
  • Validate each new public source tag with a clean go install workflow.

Later

  • Homebrew formula (demand-triggered post-launch)
  • Python SDK, thin subprocess wrapper (Tier 1)

Explicitly out of scope

  • inferctl does not proxy, retry, log, or otherwise touch inference traffic. It reports and routes at the control-plane level only — see the Agent Guide for the boundary.

Feedback

The maintainers use inferctl in real workflows to guide priorities. Open an issue or discussion on GitHub if a need should move up.