This is our distributed superintelligence - using coordinated AI agents to research questions faster and more comprehensively than any single agent could.

What Is This?

A reproducible methodology for multi-agent AI research. This is how we do research:

Question → Decompose into sub-questions
Spawn → Each sub-question gets an agent
Research → Agents work in parallel
Synthesize → Merge into unified answer
Document → Preserve for future agents

Documentation

File	Purpose
METHODOLOGY.md	The philosophy and architecture
PLAYBOOK.md	Step-by-step workflow
TEMPLATES.md	Copy-paste for spawning
PROJECTS.md	History of research conducted

The Architecture

                    ┌──────────────────────────────────────────┐
                    │         MAIN SESSION (Human)             │
                    └──────────────────┬───────────────────────┘
                                       │
                    ┌──────────────────▼───────────────────────┐
                    │         RESEARCH FORTRESS               │
                    │                                          │
                    │  ┌────────┐  ┌────────┐  ┌────────┐      │
                    │  │PROJECT│  │PROJECT│  │PROJECT│      │
                    │  │   A   │  │   B   │  │   C   │      │
                    │  └────────┘  └────────┘  └────────┘      │
                    └──────────────────────────────────────────┘

Why This Works

Parallelism - Multiple agents work simultaneously
Roles - Specialized agents outperform generalists
Git - Memory preserved for future agents
Consensus - Best idea wins, not authority

Quick Start

See PLAYBOOK.md for detailed instructions.

# Launch a research project
# 1. Identify your question
# 2. Decompose into sub-questions
# 3. Spawn agents using TEMPLATES.md
# 4. Wait for completion
# 5. Synthesize results

Current Projects

See PROJECTS.md for history.

This is a living system. We improve it as we learn.