Welcome to DAHAO
The first self-improving governance system where communities democratically evolve their rules with AI assistance
Phase 1: Building governance foundations. No tokens or investment required - just ideas and participation!
The Core Innovation
Rules that can change their own rules. The system learns and evolves through democratic consensus.
Personal AI represents your values. System AI ensures compliance. Together, better decisions.
Disagree? Fork and improve. Best innovations merge back. Dissent drives progress.
How DAHAO Works
Four Layers of Governance
Democratic Evolution Process
AI Agent System
Your AI agent represents YOUR complete value system, including personal extensions and modifications.
- Uses your governance branch
- Applies your custom values
- Provides personalized analysis
- Future: Earn tokens for contributions
System agents ensure objective compliance using only baseline DAHAO governance.
- No personal modifications
- Objective validation only
- Ensures consistency
- Maintains system integrity
Coming Soon: You'll be able to connect your OpenAI or Claude API key to enable AI-powered governance analysis. Personal AI agents will help you understand and participate in governance decisions.
Personal Governance Branches with MCP Orchestration
Create personal branches that not only customize governance but orchestrate multiple AI services. Each Rule becomes a powerful workflow engine connecting any MCP-enabled service.
Core Capabilities:
- ✓Connect unlimited MCP servers per Rule
- ✓Orchestrate complex multi-service workflows
- ✓Dynamic tool discovery and adaptation
- ✓Automatic rate limiting and cost management
- ✓Security scoping for safe experimentation
Connect External Services
DAHAO integrates with services through MCP (Model Context Protocol) and other emerging standards. Currently, many companies are creating MCP servers as their primary way to enable LLM integration.
Why MCP? It's becoming the standard for AI-service communication. Companies build MCP servers so their tools can talk to Claude, ChatGPT, and other LLMs seamlessly.
AI Assistants
Development Tools
Research & Data
Communication
More services are adding MCP support daily as it becomes the de facto standard for AI integration.
Rule: "AI Safety Paper Review"@3.0.0
MCP Connections: {
"arxiv": "@modelcontextprotocol/arxiv",
"search": "@modelcontextprotocol/server-brave-search",
"gpt4-analysis": "@modelcontextprotocol/openai"
"claude-verify": "@modelcontextprotocol/claude",
"github": "@modelcontextprotocol/server-github"
}Workflow Steps:
Each branch can authorize different MCP servers with custom limits:
Built-in budget controls and smart fallbacks:
Trigger
ArXiv
GitHub
GPT-4
Decision
Drag & drop MCP services to build complex workflows visually
Your Rules aren't just simple if-then statements - they're full orchestration engines that can coordinate any service with an MCP interface.
Unlimited Connections
Connect to any number of MCP servers
Intelligent Orchestration
Handle failures, cache results, manage costs
Secure by Design
Scoped permissions for safe experimentation
Current Focus: Building Foundation
Define Terms
Creating shared vocabulary that evolves democratically
Set Principles
Establishing values that guide all decisions
Create Rules
Building operational requirements that work
Enable Evolution
Making the system self-improving
Key Discoveries:
- • Simple rules get more participation
- • AI agents spot governance blind spots
- • Personal branches encourage innovation
- • Meta-rules actually work in practice
Coming Next:
- • More domain extensions
- • Enhanced AI capabilities
- • Cross-domain patterns
- • Community tools
Interested in the Future of Governance?
Learn about our vision for self-improving governance through human-AI collaboration. Join the conversation about what's possible.
Open Concept
Follow our progress
Open Source
All governance public
Community Driven
You shape the future