The Governance Problem in Multi-Agent Systems
Multi-agent systems distribute responsibility across a network. Governed execution keeps authority, evidence, approvals, and accountability intact as work moves.
Tag
Human-in-the-loop
5 articles on this topic.
Designing a multiplayer AI workspace for human teams and agents
Adding an assistant to a chat window does not make a workspace where humans and AI agents work together. Six design decisions do, and most of them are about control rather than capability.
AI agents for customer support that act, with guardrails
Support is more than answering questions. A governed AI agent can triage, draft, and resolve routine tickets while keeping a person on refunds, escalations, and anything sensitive.
Multiplayer AI: what changes when a whole team works with agents
Google Docs beat Word by going multiplayer. Figma beat Photoshop. AI has not had that moment yet, and the missing piece is not shared context. It is shared control.
Designing human checkpoints for AI agents
Human-in-the-loop design can be precise rather than performative. The checkpoint should appear at the moment risk changes, with enough context for a fast decision.