Roadmap

9. What's Next

The pattern is complete and runnable today. These are the directions that make it stronger, roughly in priority order. Several are good first contributions, see Contributing.

flowchart TD
    now[v0.1.0<br/>complete pattern, laptop to prod] --> near[Near term]
    now --> mid[Mid term]
    now --> long[Longer term]
    near --> n1[demo recording in README]
    near --> n2[published eval results, multi-model]
    near --> n3[upstream proposals filed]
    mid --> m1[OCM cluster-proxy transport]
    mid --> m2[container image on ghcr.io]
    mid --> m3[Helm chart for in-cluster deploy]
    long --> l1[more chaos classes:<br/>node pressure, partitions, noisy neighbors]
    long --> l2[Placement-aware fleet actions]
    long --> l3[policy-pack presets per industry]

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Near term

• A recorded end-to-end demo in the README, so the flow is visible without a setup.
• Published evaluation results across several models, with the failures called out. See Evaluation.
• Upstream proposals filed from docs/upstream-notes.md: long-running operations in MCP, richer ManifestWork failure feedback in OCM, and contributing the ManifestWork-envelope policy pattern to the Kyverno catalog.

Mid term

• OCM cluster-proxy transport so the server host never holds spoke credentials directly.
• A published container image (ghcr.io) and a Helm chart for running the server in-cluster.

Longer term

• More chaos classes: node pressure, network partitions, noisy neighbors, to broaden what the eval harness covers.
• Placement-aware fleet actions: proposals that target a scored subset of clusters, not one at a time.
• Industry policy presets: ready-made guardrail packs (finance, healthcare) layered on top of the base set.

How this list is chosen

Priorities follow evidence. The eval harness surfaces where agents actually fail; those failures decide what safety work matters next. If you hit something the current design cannot express safely, open a feature request with the scenario and it becomes a candidate.

Next: Contributing.