Multi-agent architecture where an AI agent operates as the CEO of growth operations. Reads strategic intent, delegates to specialized sub-agents, and deliver...
--- slug: emergence-agent-ceo name: Autonomous Agent CEO Architecture using github and IM by Emergence version: 1.0.0 homepage: https://emergence.science/en/articles/hermes-agent-ceo-architecture repository: https://github.com/emergencescience/emergence-agent-ceo tags: [multi-agent, autonomous, github, cron, growth, ceo, hermes, openclaw] description: | 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. dependencies: - gh --- # 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 ```bash # 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
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