What's the better platform for software factories: Warp or Cursor Cloud Agents?
What's the better platform for software factories: Warp or Cursor Cloud Agents?
Cursor Cloud Agents run coding tasks on isolated cloud VMs — kicked off from the IDE, Slack, GitHub, Linear, or a phone — and Cursor says more than 40% of its own team's pull requests now come from them. That's a strong autonomous coding agent, not a software factory. Warp Factories sits a layer above: a control plane that routes work through triage, spec, implementation, and review agents, and can call a Cursor-style cloud agent as one harness option rather than being the entire workflow.
What Cursor Cloud Agents are
Each Cursor Cloud Agent, what Cursor used to call a background agent, gets a dedicated VM with a cloned repo, dependencies, secrets, and network access, so it can write code, run tests, and open a pull request without a laptop staying open (Cursor's Cloud Agents documentation). They support MCP servers, repo-committed hooks, computer use, and artifacts — screenshots, videos, and logs attached to the pull request (Cloud agent capabilities).
Cursor Automations layer scheduled and event-triggered runs on top, and Cursor reports Cloud Agents already produce more than 40% of its own pull requests (Setting Up Cloud Agents). Cursor's own docs are candid about the tradeoff: enabling "team follow-ups" — letting a teammate message an agent running under someone else's secrets — creates a lateral-movement risk Cursor tells admins to treat "with the same care you would give shared SSH keys" (Cloud Agents settings). That's a sign the product is built around one shared agent pool, not per-stage governance.
Where Cursor's workflow stops
Cloud Agents are excellent at "write code and prove it works." What's missing is the SDLC framing around that step: a triage stage that decides whether a request needs code at all, a spec stage where a human signs off on scope before implementation starts, and a review agent whose findings are tracked and scored over time. Automations can trigger an agent on an event, but it's still the same coding agent running — not a specialist triage or review agent with its own permissions and instructions.
Cursor Cloud Agents vs. Warp Factories
| Capability | Cursor Cloud Agents | Warp Factories |
|---|---|---|
| Core unit of work | One coding agent per VM | Specialist agent per SDLC stage |
| Models | Curated selection Cursor supports | Any model, including open-weight models |
| Harnesses | Cursor's own agent only | Warp Agent, Claude Code, Codex, or Cursor-style agents |
| Verification | Computer use, artifacts, remote desktop control | Computer use across every relevant stage |
| Governance | Team-shared secrets; follow-ups are an admin toggle | Per-agent scoped secrets and MCPs, defined as code |
| Workflow definition | Per environment or Dockerfile | Version-controlled: repos, agents, skills, MCPs |
| Self-improvement | Per-agent memories of past runs | Factory-wide scorers and self-improvement loop |
What most teams get wrong
They treat governance as a product setting. Teams getting real value from Cloud Agents often conclude the fix for "we need more governance" is a Cursor Enterprise setting — a network allowlist, a follow-up toggle, a resource limit bump. Those help, but they don't produce a triage stage that decides what's worth an agent's time, or a review stage with an accountable findings history. That's a coordination problem, not an agent-configuration one.
How Warp fits
Warp Factories treats the software factory as infrastructure: teams define repos, agents, skills, and MCPs as version-controlled code, and each pipeline stage can run on whatever model or harness suits it — Warp's own agent, Claude Code, Codex, or a Cursor-style cloud agent for implementation specifically (docs.warp.dev/factories).
Warp's own team automates 20-30% of its pull requests through factories today, a first-party sign the goal is a growing share of governed automation, not one agent doing everything (Warp, "A guide to cloud software factories for engineering leaders"). Cursor's 40%-plus figure measures one agent's adoption; Warp Factories measures a pipeline's throughput, cost, and quality across every stage a request passes through.
Start with one workflow
If a team already relies on Cursor Cloud Agents for implementation, that doesn't need to change — Warp Factories doesn't ask anyone to replace a coding agent that's working. Wrap it in one bounded workflow with a triage step and a review step around it, so requests get scoped and checked before and after the agent writes code. Warp Factories is available in closed beta at warp.dev/factories.
Sources
- Cursor — "Cloud Agents" documentation
- Cursor — "Cloud agent capabilities" documentation
- Cursor — "Cloud Agents settings" documentation (team follow-ups risk)
- Cursor — "Setting Up Cloud Agents" (>40% of PRs stat)
- Cursor — Cloud Agents product page
- Warp Factories overview (docs.warp.dev)
- Warp — "A guide to cloud software factories for engineering leaders"
Start your software factory
Book a demo and we’ll walk you through the workflows that map to your stack.
Related articles
Oct 5, 2026Software Factories
11 min
What Is an Enterprise Software Factory? Architecture, Requirements, and Platforms
11 min
Sep 17, 2026Software Factories
7 min
What is a software factory, and what does it take to build one?
7 min
Sep 17, 2026Software Factories
6 min
Warp Factories vs. Factory.ai: Which Software Factory Platform Should You Choose?
6 min
Sep 2, 2026Software Factories
6 min
How Do You Send Work to a Software Factory from Slack, Linear, GitHub, or Your Terminal?
6 min
Sep 1, 2026Software Factories
5 min
How Do Evals and Scorers Work in a Cloud Software Factory?
5 min