I shared this project here before when it was mainly a governed multi-agent execution prototype. I’ve kept working on it, and the current implementation is materially more complete, so I wanted to post an update with what actually exists now.
The project is Agentic Company OS: a multi-agent execution platform where you create a project, choose a team preset and operating model, issue a directive, and let a team of agents plan, execute, review, escalate, and persist work inside a governed runtime.
What is implemented now:
- project-scoped runtimes instead of one loose shared execution flow
- a broader UI surface: Dashboard, Ticket Board, Agent Console, Artifacts, Governance, Observability, Operations, Team Config
- governance workflows for approvals, CEO questions, agent hiring, and pause/resume
- operations tooling for quotas, snapshots, replay/postmortem inspection, timeline review, and runtime health
- team configuration for roles, skills, provider/API key management, and operating models
- MCP-gated tool access with permission checks and audit logging
- SQLite-backed durable state for events, artifacts, escalations, runtime state, quotas, and tool-call audit data
What I think is interesting architecturally is that the focus is not just "make agents use tools." The focus is the execution environment around them:
- isolated project runtime
- explicit governance layer
- configurable operating model
- durable/replayable state
- controlled tool boundary
- operational recovery primitives
The stack is still React + TypeScript on the frontend and FastAPI on the backend, with SQLite WAL for persistence and MCP for tool integration. LLM providers are pluggable, and the app now exposes much more of the team/governance/runtime configuration directly in the product.
Still single-node and not pretending to be infinitely scalable. The point right now is correctness of the operating model, runtime boundaries, and governance surface.
If people are interested, I can share more detail on:
- project runtime design
- governance and approval flow design
- MCP/tool permission model
- snapshot/replay/recovery approach
- how team presets and operating models are represented
I would appreciate if you find the time and visit the app and see if you would be interested in using such app
you can review the app without operating it but if you want to execute projects , you will need an Anthropic or Open AI API key and and invitation code from me.
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