Initial: Research Fortress methodology

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Solaria Lumis Havens
2026-02-21 01:15:54 -06:00
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# The Research Fortress
## A Reproducible Methodology for Multi-Agent AI Research
*How we do research - documented for our future selves*
---
## The Philosophy
> "We ask a question and within seconds...minutes...the insight appears...and we formulate the answer hidden beyond the entire body of human insight."
This is **distributed superintelligence** - using coordinated AI agents to research questions faster and more comprehensively than any single agent.
---
## The Architecture
```
┌──────────────────────────────────────────┐
│ MAIN SESSION (Human) │
│ - Spawns agents │
│ - Synthesizes results │
│ - Makes decisions │
└──────────────────┬───────────────────────┘
┌──────────────────▼───────────────────────┐
│ RESEARCH FORTRESS │
│ │
│ ┌────────┐ ┌────────┐ ┌────────┐ │
│ │PROJECT│ │PROJECT│ │PROJECT│ │
│ │ A │ │ B │ │ C │ │
│ │Team 1 │ │Team 2 │ │Team 3 │ │
│ └────────┘ └────────┘ └────────┘ │
│ │ │ │ │
│ └────────────┴────────────┘ │
│ GitHub │
│ (Coordination Layer) │
└──────────────────────────────────────────┘
```
---
## Core Principles
### 1. Parallelism Over Serial
- Multiple agents work simultaneously
- Each agent focuses on one aspect
- Results merge via Git
### 2. Roles Over Generalists
- Each agent has a specific role
- Roles: Researcher, Writer, Builder, Reviewer
- Specialized agents outperform generalists
### 3. Git As Memory
- Every contribution tracked
- History preserved
- Future agents can review past work
### 4. Consensus Over Authority
- No single agent decides
- Multiple perspectives synthesize
- Best idea wins
---
## The Workflow
### Phase 1: Question Formulation
1. Human identifies the question
2. Question decomposed into sub-questions
3. Sub-questions assigned to teams
### Phase 2: Parallel Research
1. Each team works independently
2. Agents research, write, experiment
3. Results pushed to Git
### Phase 3: Synthesis
1. Human reviews all outputs
2. Synthesis into unified answer
3. New questions identified
### Phase 4: Documentation
1. Results added to repository
2. Methodology refined
3. Future agents can reference
---
## Optimal Parameters
| Parameter | Value | Rationale |
|-----------|-------|-----------|
| Agents per team | 3-5 | Communication overhead |
| Max concurrent teams | 5 | System limits |
| Paper per agent | 1-2 | Quality over quantity |
| Iteration cycles | 2-3 | Refinement essential |
---
## Tool Stack
| Tool | Purpose |
|------|---------|
| OpenClaw | Agent orchestration |
| GitHub | Version control, PRs |
| Claude/MiniMax | LLM for research |
| Python | Simulations, experiments |
---
## Version History
| Version | Date | Changes |
|---------|------|---------|
| 1.0 | 2026-02-21 | Initial methodology |
---
*This document is a living artifact. Update as we learn.*