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Around day six I almost went back to VS Code.
I’d been using Cursor for less than a week, and I was spending more time arguing with the AI than actually writing code. It kept suggesting completions I didn’t want, autocompleting in the wrong direction, and once it rewrote an entire function I hadn’t asked it to touch. I closed it, opened VS Code, stared at it for about thirty seconds, then opened Cursor again. I’d committed to the test.
What followed was three and a half more weeks of figuring out what Cursor actually is, as opposed to what I assumed it would be. This review is based on that.
What Cursor Is (And What It Isn’t)
Cursor is a code editor built on top of VS Code. If you use VS Code, the interface is immediately familiar, same layout, same shortcuts, most extensions carry over. The difference is that AI is built into the editor at a deeper level than any VS Code extension manages to achieve.
It’s not just autocomplete. Cursor can read your entire codebase, understand how files relate to each other, and make edits across multiple files at once based on a single instruction. That’s the thing that separates it from GitHub Copilot or the various AI extensions for VS Code. Those tools work on the file you have open. Cursor works on the project.
That distinction matters more than it sounds, and it took me about ten days to really feel it.
The First Week: Getting Out of My Own Way
The day six frustration was a me problem. I was using Cursor like a smarter autocomplete, which meant I was constantly fighting it. The tab completion kept suggesting things I didn’t want because I was writing code first and then expecting Cursor to read my mind about where I was going.
The shift happened when I started describing intent before writing code. Instead of starting to type a function and waiting for Cursor to complete it, I’d open the chat, explain what I was trying to build, and let it draft a starting point. Then I’d edit from there. That workflow felt backwards at first. By week two it was faster than anything I’d done before.
The other thing that changed things: Cursor’s Composer feature. You describe a change, it shows you a diff across every file it wants to touch, and you accept or reject. First time I used it properly, I refactored an authentication flow that touched four files in about eight minutes. That same change would have taken me the better part of an hour manually, mostly because of the cross-file coordination.
What I Actually Used It For Over 30 Days
Primarily web development work. React components, API integrations, some Python scripting on the side. Cursor handled all of it, though it was noticeably stronger on JavaScript and TypeScript than Python in my experience.
Debugging was where it surprised me most. You can paste an error message directly into the chat, Cursor reads the relevant code, and it usually identifies the problem correctly on the first try. Not always, but often enough that it became my first step for any error I couldn’t immediately spot. Faster than Stack Overflow, faster than reading docs, and it explains what went wrong rather than just fixing it silently.
Writing tests was the other area where it earned its keep. I hate writing tests. Cursor doesn’t. Give it a function, ask it to write tests, it produces reasonable coverage with actual edge cases considered. I still review everything and often tweak things, but the starting point it gives is solid. That alone probably saved me three or four hours across the month.
Documentation generation worked well for simple cases and badly for complex ones. For a straightforward utility function it produced clean JSDoc comments immediately. For a complex stateful component it generated something technically accurate but so dense it wasn’t useful. I ended up writing those manually anyway. If you’re building a broader development stack, we’ve covered complementary tools in our guide to AI tools for software engineers and our AI tools for VS Code roundup.
Pricing: What Each Plan Actually Gets You
Free tier: 2000 completions and 50 slow premium requests per month. Enough to try it seriously for a few weeks, not enough for daily professional use.
Pro at $20/month: Unlimited completions, 500 fast premium requests per month, access to the most capable models including Claude 3.5 Sonnet and GPT-4o. This is what I used for the test. The model choice matters because different models have different strengths for different tasks. I found Claude stronger for reasoning through complex logic, GPT-4o faster for straightforward completions.
Business at $40/seat/month adds team features, centralized billing, and admin controls. Worth it if you’re coordinating a development team. Unnecessary for solo work.
One thing worth knowing: the 500 fast premium requests on Pro sounds like a lot and isn’t. Heavy use of Composer on a complex project can burn through those quickly. I hit the limit twice in the last week of testing and had to drop to slower models for a day each time. Not a dealbreaker, but worth being aware of if you’re planning intensive use.
What Frustrated Me
Context limits on large codebases. Cursor indexes your project and claims to understand it, but on larger projects it sometimes loses track of how things connect. I’d ask it to make a change consistent with a pattern used elsewhere in the codebase and it would produce something that worked in isolation but didn’t match the existing patterns at all. You have to be explicit about pointing it to the right files.
It occasionally confidently produces wrong code. Not broken code, code that runs fine but does something subtly different from what you asked. The first few times this happened I didn’t catch it immediately because it looked reasonable. You cannot turn off your code review instincts just because AI wrote it. That’s the habit shift Cursor requires.
The privacy model is worth understanding before you use it on sensitive projects. By default Cursor sends code to its servers for processing. There’s a privacy mode that keeps code local, but it disables some features. If you work with proprietary code or sensitive data, read their privacy policy before committing.
Extensions compatibility is mostly fine but not perfect. About 80% of my VS Code extensions worked immediately. A few didn’t. Nothing critical, but worth checking if you rely on specific tooling. For comparison of how Cursor fits alongside other coding tools, our AI tools for programming guide covers the broader landscape.
Cursor vs GitHub Copilot: The Actual Difference
This is the question I get asked most so I’ll answer it directly. Copilot is better at inline autocomplete, the moment-to-moment suggestion as you type. It’s faster, less intrusive, and handles that specific use case with less friction.
Cursor is better at everything else. Multi-file edits, understanding your whole project, complex refactoring, debugging with context, generating entire features from a description. The gap is significant enough that I’d call them different categories of tool rather than direct competitors.
If you want better autocomplete, get Copilot. If you want an AI collaborator that can work on your project at a higher level, Cursor is the better choice. At the same $20/month price point, the decision comes down to what kind of help you actually need.
Who Should Use Cursor
Professional developers who work on projects with multiple files and need help with the coordination layer of software development. Refactoring, cross-file consistency, debugging complex issues. Cursor earns its cost quickly if that describes your work.
Solo developers and indie hackers who want to move faster without hiring. This is probably the strongest use case. The productivity gain on a well-scoped solo project is real and noticeable from week two onward.
People learning to code with some foundation already. Cursor is genuinely good at explaining what code does and why, not just generating it. That’s valuable for learning. Complete beginners may find it generates things they can’t evaluate or debug when they go wrong. For a broader look at AI tools that support developers at different stages, see our AI tools for UI development guide and our AI tools for QA roundup.
After 30 Days
I kept it. That’s the short answer.
The first week was rough enough that I nearly quit. By week two something clicked and the workflow started to feel natural. By week four I was faster on complex tasks than I’d been before, not marginally faster, noticeably faster in ways I could feel during a session.
The confidently-wrong-code problem never went away. You need to stay engaged, review what it produces, and not treat it as a black box. But that’s true of any AI coding tool. The ones that breed complacency are the dangerous ones.
For the kind of work I do, multi-file projects with real complexity, Cursor is the best AI coding tool I’ve used. The privacy considerations are worth thinking through before you start. But if your code isn’t sensitive, the productivity gain is real enough that $20/month is easy to justify.
Quick Verdict
| Best for | Professional developers, solo builders, multi-file projects |
| Price | Free / $20/month Pro / $40/month Business |
| Biggest strength | Multi-file edits and project-level understanding |
| Biggest weakness | Can produce confident but subtly wrong code |
| Replaces | GitHub Copilot for complex project work |
| Doesn’t replace | Code review, your own judgment |
| Our rating | 8.6/10 |
CognitiveFuture tests AI tools through structured real-world use over 30 days. We have no affiliate relationship with Cursor and there are no sponsored links in this article.