parallel

To run multiple AI agents in parallel for development tasks, distribute your workload across specialized agents like coder, tester, and architect. This concurrent task management significantly reduces execution time by enabling simultaneous processing within a team session.

Yes, you can assign specialized roles to concurrent agents for code review and testing. The skill supports task specialization, allowing you to distribute specific functions like QA-testing and architecture design to distinct agents based on their expertise.

The best way to speed up feature development using multi-agent concurrency is distributing sub-tasks simultaneously. Have an architect design, a coder implement, a tester write tests, and a documenter write docs all at the same time to eliminate sequential bottlenecks.

Yes, you need to configure specific prompts for different parallel agents. The skill facilitates task distribution across specialized agents with defined roles and prompts, ensuring each agent executes its designated concurrent task effectively.

Yes, parallel execution works for research tasks alongside code generation. The skill enables concurrent execution of multiple AI agents specifically for development, testing, code review, and research tasks, allowing simultaneous processing across different task types.

You should avoid using concurrent multi-agent execution for highly dependent, sequential software engineering tasks. If your workflow requires strict step-by-step validation where one phase must finish before the next begins, simultaneous parallel processing may cause integration conflicts.