# Lumbridge Compute roadmap

Lumbridge Compute is the resident AI workload control plane for unified-memory machines.

## Core contracts

1. **Models** — local vetted launch recipes with immutable revisions and measured footprints.
2. **Scenes** — named workload sets activated through admission control.
3. **Evals** — versioned datasets, prompts, harnesses, assertions, and portable results.
4. **Artifacts** — resumable weights, adapters, checkpoints, datasets, and result bundles.
5. **Jobs** — inference, evaluation, download, conversion, SFT, and RL lifecycles.

## Near term

- Resumable, checksum-verified `lumbridge-compute model pull` with leases and progress state.
- Eval comparison, regression thresholds, warmup policy, concurrency/load tests,
  server-native Prometheus metrics, and hardware/config provenance.
- Scene hooks for preflight, post-activation eval gates, rollback, and schedules.
- Gateway aliases so clients follow the active scene without configuration changes.
- Training scenes and a Prime Intellect adapter for Qwen 0.6B/1.7B experiments.
- Checkpoint discovery, pause/resume, retention, and promotion into the model registry.

## Open-source readiness

- Keep public scene/eval manifests command-free; commands remain in the trusted local registry.
- Add CI across x86_64 and aarch64, unit/integration tests, security policy,
  contribution guide, code of conduct, changelog, and versioned JSON schemas.
- Remove private hostnames, voices, paths, and finance datasets from public fixtures;
  ship generic examples and keep personal overlays outside the repository.