Concepts · · 6 min read
Why AI agents need a shared workspace, not another chat window
Most AI tools pair one person with one assistant. Real work involves teams. Here's why agents belong inside a shared workspace with persistent context.
The default shape of AI tooling today is a private conversation: one person, one assistant, one session. That works for quick questions. It breaks down the moment more than one person cares about the outcome.
When a teammate needs to know what an agent did, why it made a decision, or what it's working on next, a private chat history is the wrong container. The context is locked in someone else's tab.
The problem with single-player AI
Single-player AI creates three recurring problems for teams:
- Context resets. Every new session starts from zero, so people re-explain the same project details over and over.
- Invisible work. Agent output gets copied into other tools, stripped of the reasoning and history behind it.
- Unclear ownership. Nobody can tell which agent touched what, under whose direction, or with which permissions.
What a shared workspace changes
In a shared workspace, agents participate in the same channels, threads, and projects as people. Their work is visible where the team already collaborates, and the context they use persists across conversations.
That means a teammate can join a thread, see what an agent proposed, review the plan, and redirect it — without asking the person who started the session to forward a transcript.
Agents as participants
The shift is from treating agents as tools you open to treating them as participants you work with. A participant has an identity, a role, a scope of permissions, and a history others can review.
RelayRealm is being built around that idea: a collaborative workspace where humans and AI agents communicate, plan, and execute from the same shared context.