Cursor Review

Cursor arrived with a proposition that sounds almost irresistible: take the solid foundation of VSCode—which every developer already knows by heart—and inject a layer of artificial intelligence that truly understands your project, not just the file open in front of you. And to some extent, it delivers on that promise. The problem is that the marketing surrounding the tool sells a dream that’s a bit bigger than what the product actually delivers in practice.

The migration from VSCode is genuinely painless. Extensions, shortcuts, settings—everything migrates in minutes. This is a point that cannot be ignored because the main barrier to adoption of any new editor is precisely that initial friction, and Cursor eliminates it almost entirely. You open it, import your profile, and you’re already coding. No drama.

What really sets Cursor apart from direct competitors like GitHub Copilot is its embedding system. While Copilot works essentially with the context of the current file and a few adjacent files, Cursor indexes the entire project and builds a semantic representation of the codebase. This means that when you ask it to refactor a function, it understands the dependencies, the patterns you use in other modules, and the overall context of the application. In projects with tens of thousands of lines of code, this difference is noticeable and real.

Model flexibility is also a concrete advantage. Being able to switch between GPT, Claude, and Gemini within the same workspace provides a freedom that more closed-off tools simply don’t offer. Claude tends to perform better at long-form reasoning and complex refactorings, while other models may be faster for simple code completions. This choice comes with a cognitive cost: you need to learn when to use each one, and this adds a layer of complexity that not every developer wants to manage in the middle of a sprint.

Agent Mode is where things get interesting and frustrating at the same time. The idea of having an agent working in the background while you focus on another part of the code is powerful on paper. In practice, mastering the right prompts so the agent does what you want without going off the rails takes days of trial and error. It’s not a fatal flaw, but it’s fair to say that the learning curve exists, and Cursor doesn’t do much to smooth it out with decent documentation or onboarding.

Hallucinations are the bane of any generative AI tool, and Cursor is no exception. Suggestions for libraries that don’t exist, implementations that seem correct but have subtle bugs, imports of functions that were never defined. Anyone using the tool on autopilot will go a little crazy. Anyone using it as a collaborator who needs constant review will extract real value. This distinction is fundamental, and the tool’s marketing doesn’t make this clear enough.

The pricing model deserves special attention because it scales in a way that can catch you off guard. The free plan exists but has low limits that quickly become insufficient for professional use. The Pro plan at $20/month is reasonable for a solo developer with moderate usage. But heavy users—and this is exactly the audience Cursor benefits most—will need the Pro+ plan at $60/month. For teams, the bill adds up quickly because there’s no team license with progressive discounts: each developer pays individually. A team of five devs using Pro+ is already at $300/month, and the support you get for that amount is email and Discord with a response within 36 to 48 hours. Not even the $200/month Ultra plan offers live chat. That’s hard to justify.

The lack of native integration with GitLab and Jira is a gap that hurts especially in corporate environments. GitHub has reasonable support, but companies that run their development infrastructure outside the ecosystem may end up with a tool that doesn’t talk to the rest of the workflow. For solo devs or startups on GitHub, this isn’t a problem. For enterprises, it’s a real deal-breaker.

The tool’s Trustpilot score is 1.8, and while reviews on such platforms tend to highlight negative experiences, the number is low enough not to be ignored. Recurring complaints revolve around exactly what was identified in real-world use: slow support, unexpected billing, and expectations not managed by the company’s own marketing.

Ultimately, Cursor is a good tool for a specific user profile: a full-time developer who spends four hours or more a day in the editor, works on projects with a substantial codebase, and has the patience to learn how to work with Agent. For this profile, the ROI in time saved justifies the cost of Pro+. For hobbyists, part-time devs, teams needing support, or companies outside the GitHub ecosystem, there are cheaper, simpler alternatives with better support that deliver similar results without the premium price and the frustrations that come with it.

Using Cursor as your primary tool makes sense. Using it without reviewing the generated code is a mistake that will cost you dearly at some point. AI helps, speeds things up, and impresses in many ways, but technical judgment still needs to be human.