Cursor AI Review: Features, Context Window & Vibe Coding Workflow

Cursor is a standalone IDE built on VS Code. It adds deep AI integration for Vibe Coding. Its Composer can generate or edit multiple files in a single prompt. This review covers the context window, the Composer, and how Cursor fits into a full vibe-coding workflow. It also covers available models and key limitations.

What makes Cursor different from using VS Code with Copilot?

Cursor is a full editor, not a plugin. It embeds AI into the entire workflow. The Composer can create an entire feature folder from a single description. Copilot suggests one line at a time. Cursor generates whole files. It also provides an inline chat that sees your current selection. You edit with natural language inside the editor. The context window is larger than Copilot’s default. You can feed entire project files for coherent multi‑file edits.

How does Cursor’s Composer work for Vibe Coding?

You open the Composer with a keyboard shortcut. You describe a feature in plain language. The Composer generates all necessary files at once. It creates new folders, writes code, and wires components together. You review the diff and accept or reject changes. This is the core vibe‑coding loop in Cursor. Composer uses Claude Sonnet or GPT‑4o. Switching models helps when one gets stuck. The multi‑file awareness reduces the need to chain prompts manually.

What is the context window size and why does it matter?

Cursor supports a 200k token context window with Claude Sonnet. This means you can feed an entire medium‑sized codebase into a single prompt. A large context window lets the AI understand your project structure. It makes fewer mistakes about imports and file references. You spend less time fixing broken connections. For Vibe Coding, a big context window is essential. You describe a feature once. The AI sees all related files. It generates coherent output across your whole project[1].

Which AI models work best inside Cursor?

Claude Sonnet is the preferred model for most developers. It handles large codebases well. It produces cleaner, more idiomatic code than other models. GPT‑4o is a strong alternative for creative or complex logic. Some developers switch between models. Sonnet for structure, GPT‑4o for tricky algorithms. Cursor also supports custom API keys. You can bring your own model access. This gives flexibility for teams with specific model preferences.

What are the main limitations of Cursor?

Cursor is a desktop app. It requires local installation. It does not run in the browser like Bolt.new or Replit. Deployment is not built in. You must push to GitHub and deploy separately. The Composer sometimes over‑generates. It may create unnecessary files when a small edit is enough. Reviewing its output carefully prevents project clutter. Privacy‑conscious users should enable privacy mode. This stops code snippets from being used for training. Enterprise teams often require this setting.