This is a cross-post from alphasec.io. Original post describes itself as "the human control plane for AI labor." You define a company — give it a mission, a budget, a set of agent personas — and Paperclip runs it. Agents get heartbeats on a schedule, pick up open tasks, call their assigned large language model (LLM), and post results back as issue comments. It's effectively a project management tool where every team member is an AI agent.
Paperclip started as an experiment in running fully autonomous agentic operations at scale — "
The unit of organisation is a company. Inside a company you have agents (personas with roles, adapters, and heartbeat schedules), projects, and issues (tasks). An agent wakes up when its heartbeat fires, looks at what's assigned to it, does the work, and goes back to sleep. The idea of a pre-built company is quite powerful, and the ecosystem is slowly growing around — a managed app hosting platform that handles infrastructure, TLS, and deployments without requiring server management. If you want a VPS approach with a fixed monthly cost, the template.
External PostgreSQL (two services) — add a Railway Postgres addon and wire DATABASE_URL to ${{Postgres.DATABASE_URL}}. More robust, recommended for production. Runs ~$10-12/month. To deploy, launch the
A couple of adapters work out of the box with environment variables — no interactive login required:
| Provider | Adapter in Paperclip | Environment Variable |
|---|---|---|
| Anthropic | claude_local | ANTHROPIC_API_KEY |
| OpenAI | opencode_local | OPENAI_API_KEY |
| Gemini | opencode_local | GEMINI_API_KEY |
For Gemini, select opencode_local as the adapter and choose your model (e.g. gemini-2.5-flash) in the agent settings. The gemini_local adapter requires interactive OAuth and won't work in a Railway container. Similarly, the codex_local adapter needs WebSocket-based authentication that can't be completed headlessly — stick with opencode_local for OpenAI models.
What's Next
The deployment covered here is just the start — Paperclip running cleanly, agents wired up, ready to receive tasks. The real interesting (and fun) part lies in what you build on top of it. The GitHub repo also includes a digitalocean/ folder with a single-script VPS deployment if you prefer a fixed-cost server. I'm fascinated by the companies.sh concept, and I'm exploring a purpose-built agent company - a threat intelligence team that monitors security advisories, extracts IOCs and TTPs, and generates detection rules - as a follow up. If that sounds exciting, it'll be next.
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