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To orchestrate AI agents for complex software architecture planning, you can use a role-based collaboration protocol that assigns specialized roles like Explorer, Oracle, and Fixer to handle specific development tasks. This ensures clear division of labor and high-quality output.

The best way to manage multi-agent workflows for systematic debugging and feature implementation is by enforcing a standardized workflow with rigorous delivery contracts, ensuring input/output documentation and measurable acceptance criteria for every task.

Yes, the role-based orchestration protocol works within your local development environment and requires git as a dependency to coordinate multi-agent software development workflows and initialize the orchestrator protocol in your current project directory.

Yes, you can use specialized AI roles for architectural planning and dependency mapping during a major refactor. The Oracle defines the architectural strategy while the Explorer maps dependencies, ensuring no step is missed during implementation.

A limitation of using a structured task delegation protocol for agentic workflows is the overhead of enforcing rigorous delivery contracts and documentation standards, which may be excessive for simple, single-step modifications that do not require multi-role coordination.

Multi-agent software development requires strict input output documentation and acceptance criteria to solve the chaos of managing complex, multi-step tasks, ensuring consistent quality and verifiable results across all specialized agent roles.