Agentic OS: A 7-Layer Open-Source Architecture for Multi-Agent Coordination
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I Built an Open-Source Agent OS
Mihir N Modi developed Agentic OS to solve context fragmentation between specialized AI tools. The system unifies opencode, Hermes, and Gemini CLI into a single dashboard using a 7-layer architecture.
Why This Matters
Technical workflows often fail when switching between siloed agents for coding, research, and scheduling, resulting in lost context. Agentic OS addresses this by implementing a persistent SQLite FTS5 memory graph and a standardized Skill Hub, allowing developers to maintain a shared ‘brain’ across sessions while leveraging free-tier APIs to avoid high subscription costs.
Key Insights
- The 7-layer architecture uses an Agent Router at Layer 1 to automatically direct tasks to specialized agents like opencode or Gemini CLI, 2026.
- Persistent cross-session context is maintained via a shared brain/ folder and SQLite FTS5 memory graph.
- Skill standardization (Layer 3) utilizes SKILL.md files and automated evaluation scoring to improve agent performance over time.
- Built-in cost analytics allow users to track spending across different LLM providers from a single dashboard.
- The system uses APScheduler to manage automated jobs including system heartbeats, standups, and audits (Layer 5).
Working Examples
Quick start commands to clone and launch the Agentic OS dashboard
git clone https://github.com/modimihir07/agentic-os.git
cd agentic-os && ./install.sh && ./start.shPractical Applications
- System Monitoring: Using APScheduler within Agentic OS to run automated health audits and standup reports. Pitfall: Failing to configure the 200s AbortController, which can lead to client timeouts during long-running agent queries.
- Research & Development: Coordinating Gemini CLI for web research and opencode for DevOps tasks through a unified router. Pitfall: Manually jumping between tools without a shared brain/ folder, which results in zero-context sessions.
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