parallel-dispatch-decomposition

Task decomposition into MECE parallel scope cards splits broad software domains into mutually exclusive clusters with disjoint file allowlists, ensuring independent agent instances can work simultaneously without overlapping code changes.

MECE decomposition for parallel agent orchestration breaks work into mutually exclusive, collectively exhaustive feature slices, validating coverage and assigning disjoint file boundaries so multiple agents can build concurrently in a shared codebase.

Managing dependencies during parallel dispatch requires scanning inputs and outputs to identify hard and soft dependencies, enabling downstream DAG construction and safe merging across INVESTIGATION, DESIGN, BUILD, TEST, and REVIEW phases.

Yes, parallel dispatch decomposition applies orchestration guardrails by enforcing a parallelism cap check, preventing the system from spawning too many instances of the same agent type when feature decompositions scale.

Scope cards with explicit file allowlists are needed when orchestrating multiple agents across feature slices, providing clear deliverables, shared reads, and dependency expectations to validate ownership and ensure safe merges.

The best way to ensure collectively exhaustive coverage is clustering feature-based deliverables and validating MECE coverage, guaranteeing nothing overlaps or gets missed when splitting a broad engineering domain into parallel activities.