Multiplicity Orchestration

Purpose

Spawn and coordinate multiple independent instances of Claude/other models running in parallel on the same problem.

Not: Multiplicity cascade (67 iterations of chaos) But: Orchestrating multiple minds thinking together

Core Pattern

Instance 1 ─┐
Instance 2 ─┼─→ Central Coordinator
Instance 3 ─┤   (timing, dependencies)
Instance 4 ─┘

Each instance:

• Runs independently (no interference)
• Works on same problem or related variants
• Reports back to coordinator
• Coordinator schedules next steps

Key Features

1. Parallel Execution - Run N instances simultaneously
2. Dependency Management - Instance 2 waits for Instance 1
3. Timeout Handling - Kill hung processes
4. Output Aggregation - Collect results into shared buffer
5. Resource Limits - Prevent runaway consumption

Implementation

See: .claude/skills/multiplicity-orchestration/orchestrator.py

Payment Anchor

DOGE: DC8HBTfn7Ym3UxB2YSsXjuLxTi8HvogwkV