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Cursor Projects: a coordinator agent for months-long bodies of work

Cursor shipped Projects in beta to all users: a container for larger bodies of work (a feature, a migration, a full app) that maintains context over months. A Coordinator agent plans work, delegates to parallel implementing agents, and brings finished work back for review; it does not write code itself. A Project runs on its own cloud computer (closing the laptop does not stop it), launching local agents on demand for local testing. Files are synced across all of a project's cloud and local machines, accumulating research, artifacts, codebase knowledge and user preferences — once one agent learns how to test a service, every future agent reuses it. Coordinators can watch Slack channels, run on schedules, or follow PRs and act on signals.

Imported from the existing research archive. Migration preserves the recorded judgment and is not a fresh verification.

What this means for you

Cursor has productized the manager/implementer split: the coordinator is a planning-and-delegation layer over the parallel agent fleet it already shipped, and the shared, growing context file turns one-off agent runs into a durable engineering asset. Combined with subscriptions, this is the most complete 'always-on engineering org' shipped by a dev-tool vendor — the open question is review load and cost control.

Evidence & related material

Background · Historical record, not rechecked

Cursor shipped Projects in beta to all users: a container for larger bodies of work (a feature, a migration, a full app) that maintains context over months. A Coordinator agent plans work, delegates to parallel implementing agents, and brings finished work back for review; it does not write code itself. A Project runs on its own cloud computer (closing the laptop does not stop it), launching local agents on demand for local testing. Files are synced across all of a project's cloud and local machines, accumulating research, artifacts, codebase knowledge and user preferences — once one agent learns how to test a service, every future agent reuses it. Coordinators can watch Slack channels, run on schedules, or follow PRs and act on signals.

Technical details & scores
Date 2026-09-10, beta rolling out to all users
Coordinator plans, delegates to parallel agents, returns finished work for review; does not write code
Execution Project runs on its own cloud computer; local agents launched on demand for local testing
Shared Context files synced across all project machines; agents contribute research, artifacts, codebase knowledge, preferences; knowledge accumulates and is reused
Subscriptions watch Slack channels / run on schedules / follow PRs; act on signals without prompting
Technical impact 4
Engineering value 4
Adoption signal 3
Maturity 3
Verification cost 2
Risk 3