parallel-coding-workflow

Automating parallel execution across multiple coding tasks requires decomposing your project into smaller work items and coordinating concurrent subagents. This workflow orchestrates up to six parallel agents to handle complex multi-task development, refactoring, and batch operations.

Refactoring a large codebase across multiple microservices is best handled by breaking the task into parallelizable work items. This workflow coordinates parallel subagent execution to process multiple components simultaneously, then consolidates testing and resolves errors iteratively.

Iterative error resolution during parallel development works by consolidating testing after coding phases complete. The workflow spawns dedicated agents to fix any identified issues, repeating the cycle until all errors are resolved, ensuring robust error handling throughout.

Adapting parallelism based on system resources like CPU and memory is possible when the calculate-parallelism skill is installed. The workflow automatically detects and adjusts the number of concurrent subagents to optimize resource usage during execution.

Task decomposition for a coding workflow is needed when implementing complex features across multiple components, adopting a new API across a large codebase, or fixing a batch of related bugs across many files. It breaks large tasks into smaller, parallelizable work items.

Implementing a complex feature across frontend and backend simultaneously involves decomposing the work into parallel tasks and coordinating subagents. This workflow manages phased execution with concurrent coding agents, followed by consolidated testing and iterative error resolution.