Shared agent work
Coordinate AI agents for agencies and teams
Agencies and teams do not benefit from AI agents simply by starting as many in parallel as possible. They need shared context, explicit task owners, local access boundaries and a review path that remains understandable to clients and operators.
The practical problem
More people, repositories and client constraints increase the risk of lost context, unclear access rights and duplicate work. A clean process shows which work is ready, which is blocked and who must decide.
A concrete product-change workflow
An accountable person scopes the task and client constraints. An agent works only in the allowed local repository. Another role reviews the result and its scope. Only then does the owner decide about merge or release. The handoff records what actually happened.
What works today
The current kits provide role, routing and handoff conventions; AI Operator Bridge supports local operator work and human gates. These building blocks can be used in a small team, but they do not yet create a central hosted multi-user workspace.
Useful agency boundaries
Not every agent needs access to every repository or client material. Each task should name scope, allowed sources, protected areas, expected result and reviewer. This reduces handoff loss without promising artificial autonomy.