Cursor Review — The AI Code Editor That Changed How Developers Work

Not Just Another AI Code Tool

Cursor looks like VS Code. It’s built on VS Code. But using it for a week makes you realize it’s something fundamentally different. While GitHub Copilot adds AI suggestions to your editor, Cursor rebuilds the editor around AI as a core workflow — and the difference is significant.

After switching to Cursor full-time, the productivity improvement on real projects — not toy examples — has been the most tangible AI productivity gain I’ve experienced across any tool.

What You’re Actually Getting

Codebase-aware AI chat is Cursor’s defining feature. Ask a question about your code and Cursor doesn’t just look at the open file — it indexes your entire project and retrieves relevant context. “How does authentication work in this app?” gets a real answer referencing your actual auth files, middleware, and configuration.

Tab completions go beyond single-line autocomplete. Cursor predicts multi-line changes based on what you’re doing — if you just renamed a variable in one place, it predicts the rename in the next occurrence. If you’re writing a function similar to one elsewhere in the codebase, it suggests the pattern. The predictions feel eerily accurate.

Composer mode is where things get powerful. Describe a change in natural language — “Add a rate limiter middleware that limits API calls to 100 per minute per user” — and Cursor generates the implementation across multiple files, including the middleware, the configuration, and the route integration. You review and accept each change.

Documentation and web context can be added to conversations. Reference official docs, paste URLs, or add custom documentation that Cursor will use when generating code. This dramatically reduces hallucinated API calls and outdated patterns.

Where Cursor Genuinely Excels

Refactoring and code modifications are where the productivity gain is highest. Describing what you want changed in plain English and getting multi-file diffs back — reviewing changes rather than writing them — is a fundamentally faster workflow for experienced developers who know what they want but don’t want to manually edit 15 files.

Understanding unfamiliar codebases becomes dramatically faster. Join a new project, ask Cursor to explain the architecture, trace request flows, identify where specific logic lives. What used to take days of reading code now takes hours.

Debugging with context works because Cursor can see your error messages, the relevant code, your test files, and your configuration simultaneously. “Why is this test failing?” with the full project context produces useful answers.

Where It Falls Short

Quota management is real. Heavy users burn through Pro plan requests in 2-3 weeks. The slow model fallback when you hit limits is noticeably less capable. Power users may need the Business plan, which doubles the cost.

Composer can be overeager. Ask for a small change and occasionally get a refactored file. The “apply” workflow helps — you review every change — but it means staying attentive rather than blindly accepting.

Not for beginners learning to code. Cursor makes experienced developers faster. It doesn’t teach programming fundamentals. If you don’t understand the code Cursor generates, you’ll accumulate technical debt quickly.

Pricing Reality

Plan	Price	What You Get
Hobby	$0	2,000 completions, 50 slow premium requests
Pro	$20/mo	Unlimited completions, 500 fast premium requests
Business	$40/mo	Everything in Pro, admin controls, enforced privacy mode

The Pro plan is where value starts. Hobby is enough to evaluate whether Cursor fits your workflow.

For Middle East Professionals

For developers in the MENA region, Cursor reduces the gap between small teams and large engineering organizations. A team of 3 developers with Cursor can maintain velocity that previously required 5-6. For startups and growing tech teams across the Gulf and Levant, this productivity multiplier matters. Cursor handles comments and variable names in any language, though AI suggestions work best when codebases use English naming conventions.

Who Should Use This

Professional developers who write code daily. Tech leads managing codebases and reviewing PRs. Full-stack developers working across multiple files and languages. Anyone migrating from VS Code + Copilot who wants deeper AI integration.

Who Should Skip This

If you’re learning to code, use a standard editor and build foundational skills first. If you work primarily in Jupyter notebooks or data science, Copilot may be more appropriate. If your organization has strict data residency requirements, evaluate the privacy implications carefully.

Learn more about AI development tools in our AI Fundamentals course.