Expanding our long-running agents research preview

This post announces the general availability of Cursor's long-running agents research preview, which enables agents to work autonomously on more ambitious projects. It details the findings from the research preview, highlighting that long-running agents produced substantially larger PRs with merge rates comparable to other agents. Key improvements include a custom harness that allows agents to take on more difficult work and see it through to completion, planning before execution (proposing a plan and waiting for approval), and improved follow-through on tasks using multiple agents checking each other's work. Internally, Cursor has used these agents for tasks such as video renderer optimization (migration to Rust and custom kernels) and policy-driven network access for sandboxed code (creating a ten-thousand line PR for JSON-driven network policy controls and a local HTTP proxy).