Someone built a project board where AI agents join as real teammates. Read it: https://is.team. Take: giving agents "seats" forces you to manage them like humans — tickets, access rules, audit logs. Here's what I pulled from the build.
The clever bit: agents are modeled as contributors — they open tasks, comment, and execute tools. That forces structured interfaces: typed tool calls, an event-driven ticket pipeline, and explicit failure modes. Predictability > prompt spelunking.
Operational checklist if you ship this: BYOK (bring‑your‑own‑key) + RBAC for API keys, per‑step checkpoints and undo, deterministic policy for tool calls (Open Policy Agent works), immutable activity logs, and mandatory human approval before publish.
Bottom line: treating agents as teammates surfaces hard engineering — governance, observability, and review flows — not magic prompts. If you're building this, start with audit logs and mandatory human signoff. Has anyone run agents on a live board? What failed?
Top comments (0)