sparc-methodology

Multi-agent software development is coordinated through a structured SPARC methodology that defines orchestration modes like swarm-coordinator and workflow-manager to manage agents across specification, architecture, coding, testing, review, and deployment phases.

Cross-agent memory sharing in multi-agent orchestration is a memory integration pattern that allows development roles like researcher, architect, and coder to persist and access shared context across phases for improved consistency.

To set up a swarm coordinator workflow for feature development, configure a SPARC workflow that applies hierarchical swarm coordination to manage a structured six-step process from initial research to final deployment.

Yes, SPARC methodology supports refactoring and performance optimization by deploying specialized development modes including analyzer, optimizer, and reviewer agents backed by memory-integrated parallel collaboration.

Multi-agent orchestration using batch-executor modes utilizes a dedicated memory-manager role to handle cross-agent memory integration, ensuring shared context is properly maintained across parallel development tasks.

A multi-agent orchestration methodology like SPARC should not be used for simple single-step tasks that lack the complexity to justify end-to-end coordination across specification, architecture, coding, testing, review, and deployment phases.