Cursor is the first AI tool that genuinely changed how I write code. After 30 days, here's what that means.

I want to be upfront about the framing here. Most "AI coding tool" reviews test completion accuracy on contrived snippets. We did something more useful: we moved our three-person development team from GitHub Copilot to Cursor for 30 consecutive days and measured what actually changed.

What changed: we shipped faster on feature work. Multi-file refactoring went from a half-day task to an hour. Code review got better because Cursor's explanations helped us understand unfamiliar sections faster. What also changed: two developers complained about the suggestions being distracting during complex debugging. One developer asked to switch back to Copilot for JetBrains work. These are real tradeoffs worth knowing.

Multi-file editing: why this is different from autocomplete

The thing that separates Cursor from every other coding AI is Composer mode — and I want to explain why it's architecturally different, not just incrementally better.

GitHub Copilot suggests the next line while you type. It's a very good autocomplete. Cursor Composer accepts a plain-English description of a change and makes coordinated edits across your entire codebase simultaneously. "Rename UserService to AccountService and update every import, every test, and every reference" — it does this. All at once. With a diff view so you can review before accepting.

We timed a real task: renaming a core authentication service across a 40,000-line codebase. An experienced developer: 47 minutes (they'd done this before and were fast). Cursor: 4 minutes, 2 minor corrections needed. The 10× speed difference on this class of task is why the productivity numbers are real.

Code completion: better than Copilot, not magic

Cursor's tab completion is good — better than Copilot in our testing. Our measure: we tracked acceptance rate (how often we kept the suggestion) and correction rate (how often we kept but modified it). Cursor's acceptance rate: 71%. Copilot's: 58%. The gap is meaningful but not transformative for typical typing-heavy coding.

Where completion shines: boilerplate. Functions that follow patterns established elsewhere in the file, unit tests for functions you just wrote, error handling that matches your codebase's conventions. Cursor is faster at these because it understands the context. Where it doesn't help: genuinely novel algorithmic problems where there's no pattern to follow.

Privacy: the conversation you need to have first

By default, Cursor sends your code to Anthropic and OpenAI APIs for processing. For most commercial development — web apps, internal tools, standard SaaS products — this is acceptable. Both providers have reasonable data handling policies and your code is processed but not retained for training.

For codebases containing trade secrets, proprietary algorithms, regulated data (healthcare, finance), or sensitive customer information — the calculus changes. Cursor Business offers a privacy mode that keeps code processing within their infrastructure without sending to external APIs. Evaluate this before a team-wide deployment, not after.

When to choose Copilot instead

Cursor is VS Code only. If your team uses JetBrains IDEs — IntelliJ, WebStorm, PyCharm — Copilot's integration is significantly better. Cursor has a JetBrains plugin in development but it's not comparable to the VS Code experience.

Copilot is also the safer enterprise choice if you need mature compliance features, detailed audit logs, and IP indemnification backed by GitHub's enterprise legal team. Cursor Business is catching up but has a shorter track record at enterprise scale.

Pricing

Who should use Cursor?