parallel-session-dispatch

Parallel session management uses a coordination protocol to route feedback and resolve conflicts across concurrent AI agents. It provides naming conventions and status update rules to keep multiple Claude Code sessions synchronized without overwriting each other's outputs.

Use a parallel versus sequential decision tree to evaluate task dependencies within your master plan. It provides clear criteria to identify independent feature parts that can run simultaneously versus phases with strict dependencies requiring sequential execution.

Multi-session AI workflows require a coordination protocol defining strict branch naming conventions and status update rules. This framework tracks and merges outputs from different concurrent sessions efficiently by standardizing how each agent reports progress.

Yes, dispatching multiple Claude Code sessions from a master plan is supported. The process uses session mode mapping to select appropriate launch modes for each task and provides prompt templates to guide concurrent execution of independent features.

A key limitation of parallel AI session orchestration is conflict potential when tasks are not truly independent. If development phases share dependencies, the coordination protocol forces sequential execution, which reduces concurrency benefits and overall workflow speed.