Cursor

Cursor Review: The AI-First Editor That Rewrites How You Code

Cursor's insight was that bolting AI onto an existing editor produces a fundamentally limited experience — the AI operates on the visible file with no awareness of the surrounding codebase. By making codebase indexing and multi-file context the foundation rather than an add-on, Cursor enables AI interactions that understand how your project actually works.

Codebase Context

Cursor indexes the entire repository and makes it available as context for every chat message and generation. When you ask Cursor to add a new API endpoint, it understands the existing router patterns, middleware stack, and data model in your codebase — suggesting implementations consistent with how your project is already structured rather than generic boilerplate. The @codebase, @file, and @symbol references in chat explicitly pull relevant context into any conversation.

Composer for Multi-File Edits

Composer is Cursor's most powerful capability: describe a feature, refactor, or architectural change in natural language, and Cursor plans and executes edits across multiple files simultaneously — showing a diff for review before applying. A request like 'add email verification to the user registration flow' results in changes to the auth service, email service, registration handler, and test file in a single operation.

Tab Completion

Cursor's Tab completion goes beyond token prediction — it anticipates where the next edit should be and moves the cursor there, enabling rapid multi-location refactors by accepting a series of predicted changes with Tab presses through a file.

Score: 9.1/10 — Best multi-file AI coding experience; editor migration cost and higher price than Copilot are the considerations.