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Parallel agent orchestration involves generating a project plan with a dependency DAG, dispatching agents into isolated worktrees, and auto-merging their changes upon completion. This allows multiple coding tasks to execute simultaneously with structured progress tracking.

A dependency DAG is a Directed Acyclic Graph that enforces task execution order based on dependencies. It automatically dispatches subsequent coding missions only after prerequisite tasks finish, preventing merge conflicts in parallel agent workflows.

You isolate parallel coding agents by dispatching them into isolated worktrees. Each agent receives full tooling access within its dedicated worktree, executing tasks independently before auto-merging completed changes back to the main project branch.

Yes, multi-agent progress tracking is handled via reports, statuses, and dashboards. The system produces standardized reports for auditing and review, tracking each agent's mission throughout the parallel execution lifecycle and auto-dispatching dependent tasks.

The best way to manage auto-merge workflows for parallel REST API development is to use an orchestration system that enforces a dependency DAG and dispatches agents into isolated worktrees. This allows modular features to be implemented in parallel and merged automatically.

You should avoid parallel multi-agent dispatch when coding tasks lack clear dependency boundaries or require strict sequential execution. If tasks cannot be isolated into separate worktrees or need continuous manual intervention, agent orchestration overhead outweighs its parallel execution benefits.