orchestrator

You can coordinate end-to-end AI feature pipelines by dispatching subagents for dev, code-review, qa, and audit tasks in batched launches. The orchestrator enforces loop caps and tracks state to maintain traceability across the full dev-to-qa lifecycle.

Gating development handoffs requires a mandatory audit stage that checks a mechanical audit trail before delivery. This approach guarantees a single consolidated handoff only after the audit gate passes, ensuring full traceability for compliance and post-mortem analysis.

You can resume an interrupted AI development session by running the orchestrator with the --resume flag. It tracks pipeline state in a session file and handles partial failures using defined retry and escalation policies to recover the workflow.

You need hook-based safeguards when dispatching AI subagents to enforce reference contracts and maintain safety. These safeguards include dispatch-manifests, model calibration, and handoff rules to ensure recoverability and traceability during autonomous pipeline orchestration.

Yes, you can batch dispatch multiple AI agents in a single turn for feature development. The orchestrator launches dev, logic-reviewer, and blocker-specialist agents simultaneously to accelerate the pipeline while enforcing strict execution caps.

Limitations of autonomously orchestrating full dev-to-qa lifecycles include strict loop caps that terminate runaway processes and reliance on predefined failure-modes policies. Partial failures require manual restarts or escalations if automated retry limits are exceeded.