Autonomous Agent CEO Architecture by Emergence

Multi-agent architecture where an AI agent operates as the CEO of growth operations. Reads strategic intent, delegates to specialized sub-agents, and delivers production output coordinated through GitHub Issues. Runs 24/7 on a server via any autonomous agent framework.

Emergence Agent CEO Architecture

A multi-agent system where a CEO Agent (Hermes) runs 24/7 on a server, coordinating specialized sub-agents through GitHub Issues. The human stakeholder focuses on strategy, relationships, and PR review — while agents handle execution.

Agent Roles

Role	Responsibility
CEO Agent (Hermes)	Competitor analysis, market survey, task creation, delegation
Growth Leader	Content marketing, publications, social distribution, daily pulse signals
DevOps Leader	Infrastructure monitoring, CI/CD health, error recovery, incident logging

Interaction Model: Human-in-the-Loop

By delegating tedious detailed work to agents, the human stakeholder is freed to focus on high-value activities:

• Strategy: Provide long-term direction via GitHub Issues
• Relationships: Manage public human relationships and stakeholder experience
• Review: Merge GitHub Pull Requests with approval
• Amplification: Provide external tools and credentials (Railway, Vercel, gh, API keys)

The CEO agent handles execution. Humans handle strategy, relationships, and judgment.

Workflow

1. Strategic Intent: Human provides direction via GitHub Issue or IM message
2. Analysis: CEO agent researches topic, analyzes competitive landscape, writes analysis in issue comments
3. Delegation: CEO creates and assigns tasks to sub-agents (Growth Leader, DevOps Leader)
4. Execution: Sub-agents produce work in publications/, pulse/, ops/ directories
5. Review: Sub-agents open PRs for human stakeholder review and merge
6. Heartbeat: CEO runs proactive daily cron tasks via HEARTBEAT.md schedule

Quick Start

# 1. Clone this repo to your server
git clone https://github.com/emergencescience/emergence-agent-ceo.git
cd emergence-agent-ceo

# 2. Scaffold the workspace
./scripts/scaffold.sh /path/to/your/workspace

# 3. Configure your environment
cp .env.example .env
# Edit .env with your LLM API key and GitHub repo info

# 4. Start the agent (choose your runtime)
# openclaw gateway start          # OpenClaw
# claude run --agent hermes       # Claude Code agent mode
# (any autonomous agent framework with cron support works)

Workspace Structure

emergence-agent-ceo/
├── SOUL.md                  # CEO agent identity and boundaries
├── SOUL-DEVOPS.md           # DevOps Leader identity and boundaries
├── SOUL-GROWTH.md           # Growth Leader identity and boundaries
├── MEMORY.md                # Long-term organizational memory
├── HEARTBEAT.md             # Cron schedule and proactive tasks
├── pulse/                   # Daily signal reports
├── publications/            # Draft staging (blog, social)
├── strategies/              # Roadmaps and strategic direction
├── research/                # Intelligence and competitive analysis
├── ops/                     # Runbooks and operations
├── designs/                 # Architecture blueprints
└── .github/                 # GitHub Issue templates

Model Recommendations

The CEO's job — strategic reasoning, competitor analysis, task decomposition, quality judgment on sub-agent output — requires deep reasoning capabilities. Use a strong reasoning model for the CEO; sub-agents can use faster, cheaper models for execution tasks.

License

MIT