ralphinho-rfc-pipeline

You can break down large feature requests by using RFC decomposition to automatically split them into a Directed Acyclic Graph (DAG) of work units. Each unit represents an independently verifiable task with defined dependencies for structured execution.

RFC decomposition automatically breaks down high-level feature requests into a Directed Acyclic Graph (DAG) of manageable work units. This allows complex software development tasks to be divided into independently verifiable units with defined dependencies.

Quality gates across multiple agents are enforced through strict validation stages applied to every work unit, including research, implementation, and review phases. The pipeline also implements merge queue logic to ensure system integrity across complex multi-unit workflows.

Yes, you can coordinate multiple agents to build a microservice by decomposing the feature into a dependency-aware sequence. This allows separate agents to handle database schema design, API implementation, and security testing in a structured workflow with integration validation.

A DAG-based pipeline is needed when managing large-scale feature development that exceeds the capacity of a single AI pass. It breaks work into independently verifiable, manageable units with defined dependencies to maintain system integrity across complex multi-unit workflows.

The pipeline requires features to be decomposable into a DAG of verifiable units and depends on strict quality gates for validation. It is designed for complex, large-scale workflows rather than simple tasks that a single AI pass can complete.