Cursor

Video Review

About

Cursor is an AI-native code editor built on top of Visual Studio Code that deeply integrates large language models into every aspect of the development workflow. Unlike traditional editors with bolt-on AI plugins, Cursor was architecturally designed around AI from the ground up, offering intelligent code completion, multi-file editing, autonomous agents, and full codebase understanding out of the box. At its core, Cursor features a proprietary Tab model that delivers context-aware autocomplete by predicting not just the next token but the developer's next action with striking accuracy and speed. The Agent mode takes this further by operating autonomously — building, testing, and demoing features end to end for the developer to review. Composer enables multi-file edits from natural language prompts, making large refactors and feature implementations dramatically faster. Cursor supports every major frontier model including Claude Opus 4.6, GPT-5.2, Gemini 3 Pro, and xAI's Grok Code, as well as Cursor's own proprietary models. Developers can choose the best model for each task or bring their own API keys for maximum flexibility. The editor provides complete codebase understanding through semantic indexing that scales to massive enterprise codebases. Additional capabilities include BugBot for automated GitHub pull request reviews, cloud agents accessible from any browser, MCP (Model Context Protocol) app integrations, Slack integration for team collaboration, and CLI support. Cursor is trusted by over half of the Fortune 500 and reports over 90% adoption at companies like Salesforce and NVIDIA. With SOC 2 certification, enterprise-grade security controls, and team collaboration features, Cursor has rapidly become the leading AI code editor for both individual developers and large engineering organizations.

Key Features

• AI-powered Tab autocomplete with next-action prediction
• Autonomous Agent mode for end-to-end feature building
• Composer for multi-file editing from natural language
• Support for Claude, GPT, Gemini, Grok, and proprietary models
• Complete codebase understanding via semantic indexing
• BugBot automated pull request code review
• Cloud Agents accessible from any browser
• MCP app integrations and tool marketplace
• GitHub, Slack, and CLI integrations
• Shadow workspaces for safe experimentation
• Custom API key support for model flexibility
• Enterprise SSO, SCIM, and role-based access control

Use Cases

• 1Rapid prototyping and feature development with AI agents
• 2Large-scale codebase refactoring across multiple files
• 3Automated code review and bug detection on pull requests
• 4Onboarding to unfamiliar codebases with semantic search
• 5Pair programming with AI for complex implementations
• 6Enterprise team collaboration with shared rules and commands
• 7Debugging and fixing issues with contextual AI assistance
• 8Writing boilerplate code and tests from natural language prompts