deployless

AI PR intake and multi-agent governance for deployless repositories. Use when a repo has high-volume bot or agent PRs, parallel agent work, noisy low-context PRs, merge-queue pressure, CI exhaustion, duplicate fixes, ownership confusion, or review bottlenecks that threaten a single-mainline delivery model.

Deployless delivery-model audit. Use first when adapting any repository toward single-mainline development, automatic deployment from main, runtime release controls, production-trace-driven iteration, AI PR governance, or multi-agent delivery workflows.

Single-mainline governance for deployless repositories. Use after a deployless audit when a repo needs trunk-based branch rules, branch protection, contribution guidance, review gates, merge queue policy, AI PR intake rules, or agent-ready mainline practices.

Operational safety for deployless repositories. Use after mainline deployment and runtime release controls are designed, when a repo needs traces, replay tests, observability, rollback drills, smoke checks, compatibility windows, or expand-contract migration safety.

Continuous production path for deployless repositories. Use after mainline governance and release controls exist, when a repo needs CI/CD changes to automatically deploy, publish, or promote artifacts from main across any language, runtime, or hosting platform.

Runtime release controls for deployless repositories. Use when a repo needs feature flags, kill switches, capability gates, targeted rollout, remote config, routing rules, or a provider-neutral release-control facade independent of language and provider.