dev-competition

Blind parallel AI competition is a process where two implementers independently generate artifacts in isolated workspaces, and a Judge evaluates both to select the best result. This structured evaluation drives robust learning and convergence by avoiding bias.

To set up a multi-agent blind competition, assign roles for Implementer A, Implementer B, and Judge, then initialize Phase 1. Implementers operate in separate directories like impl_a/ and impl_b/ under a managed competition space.

Yes, you can use multi-agent orchestration to compare independent AI implementations. Two implementers work in isolated spaces to generate parallel artifacts for the same requirement, enabling blind comparison and formal judgment to guide improvements.

Artifacts are submitted via designated directories to enforce role isolation. A Judge then compares the implementations against a clear requirement and produces a formal judgment protocol to extract learnings and guide future work.

A limitation of blind parallel evaluation is its strict requirement for isolated workspaces and role separation. It requires phase-based execution and cannot support collaborative artifact generation between implementers during the competition phases.