If you’re comparing Windsurf vs Cursor, you’re probably trying to answer a simple question: which one will make me ship faster without turning my codebase into mush?
They overlap a lot (AI chat, inline edits, multi-file refactors). The useful differences are less about marketing and more about workflow: how much autonomy you want to give the tool, how you review changes, and where your code actually runs.
The short version
Pick Cursor if you:
want an IDE-first experience with predictable, reviewable edits
are already comfortable in the VS Code ecosystem
care about tight iteration loops on an existing repo
Pick Windsurf if you:
want a more “agentic” workflow (bigger delegated tasks, more autonomy)
are happy to spend a bit more time steering and reviewing
like the idea of the editor acting like a junior dev you supervise
If you’re unsure: start with Cursor for day-to-day coding, and treat Windsurf as a “bigger swings” tool for scaffolds, migrations, and one-off refactors.
What matters more than the editor: where your code runs
Most people evaluate these tools as if the code lives on their laptop. But if you’re doing serious work—larger repos, bigger models, long-running services—your bottleneck becomes:
compute (CPU/RAM/GPU)
network + environment drift
privacy / where code gets sent
how repeatable your setup is across machines
A practical pattern is:
Put the repo and runtime on a remote Linux machine you control (so the environment is stable)
Connect your editor to that machine
Let the AI work against the real filesystem and services
On Zo Computer, that “remote machine” is your own always-on server, with built-in file storage, terminal, and agent automation.
Remote IDE setup: https://www.zo.computer/tutorials/how-to-connect-your-ide-to-a-remote-server
Zo agents (automation you can schedule): https://docs.zocomputer.com/agents
A decision checklist (use this, not vibes)
1) How do you want changes to land?
Small, constant edits (rename, extract function, fix types, update tests): favour the tool that makes it easiest to review and iterate.
Big delegated tasks (scaffold a feature, migrate a framework, “make this work end-to-end”): favour the tool that can hold a bigger plan.
2) How strict is your review process?
If you’re operating with:
CI requirements
mandatory PR review
tight security constraints
…optimise for a workflow where the AI’s output is naturally “diff-first” and easy to verify. If your process is looser, you can benefit more from agentic autonomy.
3) How much context do you need per request?
For monorepos and complex systems, you’ll hit “context wall” problems. In practice, you’ll want:
strong search/navigation (jump-to-symbol, ripgrep, etc.)
repeatable scripts and tasks
an environment where you can run tests and services continuously
That’s why pairing either editor with a stable remote environment matters.
How to use Cursor or Windsurf with Zo (recommended setup)
This is the workflow that tends to work best in practice:
Put your repo on Zo (clone/pull there)
Connect your editor via SSH so files, builds, and services all run on Zo
Run your dev server / tests on Zo and keep them running
Use the AI to propose changes, then verify with:
tests
linters
typecheck
a quick manual smoke test
If you want the editor experience in a browser (no local installs), you can also run VS Code in your browser on Zo.
Browser-based dev: https://www.zo.computer/tutorials/how-to-run-vs-code-in-your-browser
Practical comparison: what you’ll notice day-to-day
Speed of iteration
The “best” tool is the one that lets you do this loop fast:
ask for a change
inspect the diff
run tests
refine
If you find yourself spending time undoing broad edits, you’re using an autonomy level that’s too high for the task.
Multi-file refactors
For either tool:
be explicit about constraints (“don’t change public APIs”, “keep behaviour identical”)
ask for incremental steps (“first add tests, then refactor, then optimise”)
require a final checklist (“what files changed, what commands to run, what risks remain”)
Running code (the hidden differentiator)
AI edits look impressive until you’re dealing with:
flaky integration tests
services that need env vars
database migrations
long-lived processes
Running everything on Zo reduces “works on my machine” drift and makes the AI’s job easier because it can actually execute and iterate against the real environment.
A safe way to evaluate (1 hour test)
Take a real repo and run the same task in both:
Add a small feature behind a flag
Write/extend tests
Refactor one messy module
Score each tool on:
how often it surprises you (bad surprises matter)
how easy it is to review and control the changes
how many iterations it needs before passing tests
Keep the task identical. Don’t let one tool “choose a different architecture” unless you explicitly asked.
Summary
There isn’t a universal winner in Windsurf vs Cursor—the winner depends on how you ship.
Cursor tends to shine for tight, reviewable iteration.
Windsurf tends to shine when you want bigger delegated chunks of work.
For both, you’ll get better results if your repo and runtime live on a stable remote environment (like Zo), and your editor connects in.
Relevant Zo docs:
Tutorials index: https://www.zo.computer/tutorials
Tools overview: https://docs.zocomputer.com/tools