What we’ve learned building cloud agents
Cursor shares one year of lessons from building cloud agents. The biggest takeaway: a cloud agent's output quality depends almost entirely on having a full development environment. Unlike local agents that inherit your laptop's environment, cloud agents need it reconstructed from scratch. This led to building VM hibernation/resumption pipelines, checkpoint/restore/fork mechanisms, secret redaction, network policies, and credential management — essentially enterprise IT for agents. For reliability, early work-stealing architecture managed only one 9 of uptime. Migrating to Temporal's durable execution framework pushed past two 9s, handling over 50 million actions per day across 7 million+ unique workflows, with 40%+ of Cursor's own PRs now coming from cloud agents. Critical architectural decision: decoupling agent loop, machine state, and conversation state allows agents to run across different pod types and subagents to outlive parents. Another insight: as models improve, move logic out of the hardcoded harness into tools the agent controls (e.g., GitHub CLI, Playwright). The post also discusses current harness for computer use and future self-healing environments (autoinstall).