Cursor

Overview

Cursor is an AI-powered code editor designed to significantly enhance developer productivity by integrating advanced artificial intelligence features directly into the coding environment. Cursor offers a suite of capabilities, including intelligent code completion, natural language editing, and a deep understanding of codebases, positioning it as a potential catalyst for improving efficiency and code quality within engineering teams. 

This report provides a detailed evaluation of Cursor across several critical dimensions, encompassing its fundamental characteristics, functional capabilities, privacy and security considerations, pricing structure, and the reported impact it has on the software development lifecycle. The analysis aims to equip engineering leaders with the necessary information to make informed decisions regarding the adoption of Cursor within their organizations.

Cursor distinguishes itself from similar AI coding tools through a combination of deeply integrated AI features and a user-friendly environment. As an AI-powered Integrated Development Environment (IDE), it offers a comprehensive coding experience enhanced by artificial intelligence. One of its primary differentiators is its intelligent tab completion, which goes beyond simple suggestions by predicting the next edit and often anticipating entire lines or blocks of code. This feature is frequently lauded as being exceptionally intuitive and a significant improvement over traditional autocomplete functions.

Another key differentiator is Cursor's robust codebase knowledge. The tool can understand and answer questions about the entire project, allowing developers to quickly retrieve information or refer to specific files and documentation. The natural language editing capability enables users to write code using plain English instructions, facilitating rapid updates and modifications.

Compared to other AI coding assistants, Cursor offers unique advantages. Its new agent mode can autonomously generate code across multiple files and run shell commands, streamlining complex tasks. The multi-tabbing feature allows for applying related changes across various locations in the code. Cursor also provides robust and flexible context management, enabling the inclusion of diverse resources like documentation sets, specific web pages, and git history. Furthermore, it can automatically generate commit messages, respecting custom rules defined by the user.

Cursor is recognized for its superior performance in code completion speed and reliability, robust collaboration features, and advanced refactoring capabilities. The ability to seamlessly integrate multiple AI models and even utilize local models further sets Cursor apart. Its focus on providing a holistic project understanding and an integrated development flow contributes to significant productivity gains. The extensive list of features, including AI-powered code completion, natural language editing, code chat, smart refactoring, and an AI terminal, underscores its comprehensive approach to AI-assisted coding. Finally, its custom LLM architecture, enabling long-context processing and diff-aware predictions, distinguishes it as a powerful tool designed for modern software development.

Functionality

Interaction

Autocomplete

Cursor incorporates a highly effective code autocomplete feature that goes beyond simple word completion. It intelligently predicts the user's intended code, often suggesting complete lines or even multi-line blocks. This prediction capability continuously learns from the user's recent changes, adapting its suggestions to the evolving context of the code. The accuracy of this feature has been described as exceptional, sometimes anticipating the developer's next step with surprising precision.

The technology behind this autocomplete includes a "Fusion model", which provides near-instant and highly accurate suggestions for both completing code and navigating to the next logical editing position. This model represents a significant advancement, improving upon earlier iterations in terms of prediction accuracy, the length of suggested code changes, and overall responsiveness.

Cursor offers diff-aware predictions, which present the suggested code changes as a diff, clearly showing what will be added, modified, or removed. This is particularly beneficial during refactoring tasks. The "predictive editing" feature takes this a step further by anticipating where the developer might want to edit next, allowing for a more fluid and intuitive coding experience where the AI feels like a natural extension of the developer's thought process.

Agent Mode

‍Cursor's Agent mode represents a significant enhancement in AI-assisted coding. This mode is designed to handle complete tasks from initiation to completion, all while keeping the developer in the loop. Accessible through the 'agent' selection in the Compose, this feature aims to provide a more unified and powerful AI experience by integrating functionalities that were previously separated, such as chat and code composition.

A key aspect of the Agent mode is its ability to automatically discern the necessary context for a given task. By utilizing custom retrieval models, the AI can understand the codebase, reducing the need for developers to manually specify context files. The Agent can also autonomously write and execute terminal commands, typically prompting the user for confirmation before execution to ensure safety and control. Moreover, it can detect and automatically fix linting errors, minimizing the need for manual debugging.

The evolution of Agent mode has seen it become the default interaction within Cursor, reflecting its enhanced capabilities. It can automatically search the web for current information without requiring explicit @Web commands from the user, further streamlining the process of gathering necessary context for coding tasks. This mode can also generate code spanning multiple files and intelligently determine the required context, making it a powerful tool for complex development scenarios. For users who require a more hands-off approach, the "YOLO mode" allows the Agent to automatically execute terminal commands, install packages, and even attempt to fix errors based on the output, though this feature comes with significant warnings regarding potential risks.

Chat-Based Assistance

‍Cursor provides comprehensive chat-based assistance that is deeply integrated with the user's codebase. This chat interface allows developers to communicate with an AI that has a contextual understanding of their project, including the currently open file and the cursor's position. This enables users to ask specific questions about their code, such as identifying potential bugs, and receive contextually relevant answers.

To further enhance the chat's awareness, users can select specific blocks of code and add them as context using shortcuts like Ctrl+Shift+L or the "@." symbol. For broader queries, developers can engage the AI with their entire codebase by using Ctrl+Enter or the "@Codebase" command. The chat supports instant application of suggested code changes back into the codebase with a simple click on the play button located at the top of any chat code block.

Beyond code-specific queries, the chat functionality allows users to reference code within their project using "@" symbols, providing the AI with additional context. It also supports the inclusion of visual context through images, which can be added by clicking the image button or dragging an image into the input box. For information beyond the codebase, the "@Web" command enables the AI to search the internet for up-to-date information, and users can reference popular libraries or add their own documentation using "@LibraryName" or "@Docs". 

Terminal Access‍

Cursor has the capability to automatically write and execute terminal commands, offering a streamlined approach to interacting with the system directly from the IDE. By default, Cursor prompts the user for confirmation before running any terminal command, providing a layer of control and preventing unintended actions.

In addition to automatic execution, Cursor features a "Terminal Cmd K" functionality. By pressing Ctrl/⌘ K within the built-in Cursor terminal, a prompt bar appears at the bottom, allowing users to describe their desired terminal action in plain English. The AI then generates the corresponding terminal command. Users can choose to accept the command by hitting Esc or run it immediately by pressing Ctrl/⌘ + Enter. This feature leverages the recent terminal history, user instructions, and any text entered in the prompt bar as context for generating the appropriate command.

Furthermore, the Agent mode in Cursor can automatically execute Model Context Protocol (MCP) tools, particularly when the "Yolo mode" is enabled. This allows for even more automated interactions with the underlying system. 

Integration

‍Supported Platforms and Development Environments

Cursor is designed to be a cross-platform integrated development environment, supporting major operating systems including Windows, macOS, and Linux. A significant aspect of its design is that it is built as a fork of the widely used Visual Studio Code (VS Code). This foundation provides developers with a familiar user interface and ensures a relatively low learning curve for those already accustomed to the VS Code environment.

One of the key benefits of being a VS Code fork is the seamless integration with the existing VS Code ecosystem. Cursor allows users to import their preferred extensions, themes, and keybindings with a single click. This compatibility ensures that developers can maintain their established workflows and coding preferences while using the AI-powered features of Cursor. 

‍Supported Languages and Frameworks‍

Cursor offers broad support for a multitude of programming languages, covering many of the most popular and widely used options in the industry. While it is designed to be compatible with most popular programming languages, it particularly excels with JavaScript, Python, and TypeScript due to the extensive training data available for these languages. Beyond these, Cursor also supports Java, C++, C#, Ruby, Go, Rust, Swift, C, and PHP.

In terms of frameworks, Cursor seamlessly integrates with major JavaScript frameworks and libraries, including React & Next.js, Vue.js, Angular, and Svelte. It also provides excellent support for backend frameworks such as Express and NestJS. The "awesome-cursorrules" GitHub repository serves as a testament to the wide-ranging support for various frameworks and languages, showcasing community-driven configuration files that help tailor Cursor's behavior to specific technology stacks. 

Supported LLM Providers and Models‍

Cursor provides users with a rich selection of Large Language Model (LLM) providers and models, offering flexibility in choosing the AI engine that best suits their needs. Supported providers include OpenAI, Anthropic, Google, and xAI 31. Within these providers, users can access a variety of models such as OpenAI's GPT-4o, GPT-4, GPT-3.5, o1, o1-mini, and o3-mini; Anthropic's Claude 3.7 Sonnet, Claude 3.5 Sonnet and Haiku, and Claude 3 Opus; and Google's Gemini. Additionally, Cursor features its own custom model, "cursor-small", and supports models from Deepseek (R1 and v3) through the Fireworks platform. Support for xAI's Grok-2 is also available.

Users have the ability to easily switch between these different models within the Cursor settings, allowing them to optimize for factors such as speed, reasoning capability, and cost. For added convenience, Cursor offers an "Auto-select model" feature that intelligently chooses the most appropriate premium model based on the task at hand and model availability.

Custom LLM Support‍

Cursor offers the flexibility for users to integrate their own API keys for several prominent LLM providers, including OpenAI, Anthropic, Google, and Azure. This feature allows developers to leverage their existing subscriptions or specific pricing arrangements with these providers directly within the Cursor environment.

To use a custom API key, users can navigate to the "Models" section in Cursor Settings, enter their API key, and click the "Verify" button ⁴⁰. Once the key is validated, it will be enabled for use. It is important to note, however, that certain Cursor features, such as Tab Completion and potentially Agent mode for some models, rely on specialized models and may not function with custom API keys. Furthermore, OpenAI's reasoning models like o1, o1-mini, and o3-mini currently require specific configurations and are not compatible with custom API keys. Cursor primarily supports API providers that are compatible with the OpenAI API format, such as OpenRouter, and does not offer support for custom local LLM setups or other proprietary API formats.

Awareness

Context from Non-Code Sources‍

Cursor can integrate context from non-code sources through the Model Context Protocol (MCP). MCP serves as a universal interface that allows AI assistants to interact with external data sources and APIs. Platforms like Ragie offer MCP servers that act as a bridge between AI tools like Cursor and services such as Jira, Google Drive, and Slack. This integration allows Cursor to retrieve and utilize information from these external sources, providing a richer context for its AI-powered assistance.

Public Documentation‍

Cursor excels in its ability to reference public documentation, providing developers with immediate access to a wealth of information without needing to leave the IDE. The "@LibraryName" command allows users to directly reference documentation for popular libraries, while the "@Docs → Add new doc" feature enables the integration of custom documentation sources. This functionality supports various formats, including converting PDF documents into text for indexing and referencing. Developers can extract content from public GitHub repositories, such as README files and code examples, and add them as documentation within Cursor. The "getcursor/crawler" repository on GitHub maintains the official list of built-in documentation sources, which are automatically updated on a weekly basis, ensuring users have access to the latest information for a wide range of technologies.

Web Search‍

Cursor incorporates a highly convenient feature that allows developers to search the web for answers directly from within the IDE. By using the "@Web" command followed by their query, Cursor intelligently constructs a search query based on the context of the user's current work and the query itself. This seamless integration of web search provides developers with access to the vast resources of the internet, enabling them to find up-to-date information, explore solutions to problems, and learn about new technologies without the need to switch applications. In the Agent mode, this web search capability is even more integrated, with the AI automatically performing searches when it requires current information or additional context to complete a task.

‍Images as Context

Cursor allows users to incorporate images to provide visual context within chat interactions. This feature can be accessed by clicking the dedicated image button located under the chat input area or by simply dragging an image file directly into the input box.The inclusion of visual information can be particularly beneficial in scenarios where a textual description might be insufficient, such as when discussing user interface elements, error screenshots, or diagrams related to the code. 

‍Fine-Tuning

Cursor offers ways for teams to tailor its behavior and ensure adherence to their specific coding styles. Developers can define custom instructions within the "Rules for AI" section in Cursor's settings. These rules act as a foundational prompt that guides the AI's code generation and suggestion processes. For more granular control at the project level, teams can utilize a .cursorrules file located in the root directory of their project. This file allows for project-specific instructions, ensuring that the AI's assistance aligns with the unique conventions and best practices of each codebase. Project rules can be configured to apply to specific file paths, offering even finer-grained control over the AI's behavior in different parts of the project. Examples of such rules include enforcing particular naming conventions for variables and functions, prioritizing code readability, or requiring specific error handling patterns. These rules are automatically considered by the AI when it interacts with the relevant files.

‍Codebase Context 

Cursor is engineered to possess a deep understanding of project architecture. It employs custom retrieval models that help it analyze and comprehend the entire codebase, including its structure, dependencies, and the relationships between different components. This comprehensive understanding allows Cursor to provide more contextually relevant and accurate suggestions that are in line with the project's overall design and architectural patterns. Unlike some other AI coding assistants that primarily focus on individual files, Cursor maintains a broader perspective, considering the entire application's context. This capability is particularly beneficial for tasks such as cross-file refactoring, where the AI needs to understand how changes in one part of the codebase might affect other areas. By analyzing the codebase, Cursor can adapt its suggestions to match the existing architectural style and conventions, making it a more integrated and helpful tool for developers working on complex projects.

Leverage Multiple Files

Cursor is designed to effectively leverage multiple files when generating code, a capability that is crucial for handling complex development tasks. Its "Agent" mode is specifically engineered to generate code that spans across several files, allowing it to implement features or perform refactorings that involve modifications in various parts of the codebase. Similarly, the "Composer" feature provides a powerful interface for multi-file editing and even the generation of entire applications based on user descriptions. This allows developers to provide high-level instructions, and Cursor can then orchestrate the necessary changes across the relevant files. Users can explicitly include multiple files or entire folders as context for the AI when prompting it to generate or modify code by utilizing features like "@Files" and "@Folders". 

Privacy and Security

SOC 2 Compliant

Cursor is SOC 2 Type II certified. This certification indicates that Cursor has undergone a thorough audit by an independent third party and has demonstrated that it meets high standards for data security, availability, processing integrity, confidentiality, and privacy. Organizations considering using Cursor can request a copy of the SOC 2 report from trust.cursor.com to gain a deeper understanding of their security controls and practices.

Code Retention Policy

Cursor's code retention policy is governed by its "Privacy Mode" setting. When Privacy Mode is enabled, Cursor guarantees zero data retention, ensuring that user code is not stored on their servers or used for model training by Cursor or any third parties. In this mode, user code is only processed temporarily to fulfill the AI request and is then deleted. Privacy Mode is enforced by default for users on the Business plan and can be enabled by users on the Pro and Hobby plans.

If Privacy Mode is disabled, Cursor may collect telemetry and usage data, which could include prompts, editor actions, and code snippets, to help improve its AI features. However, even without Privacy Mode, when users choose to index their codebase for enhanced context, the plaintext code is not permanently stored; instead, it is used to compute embeddings, and the plaintext code ceases to exist after the request is processed. These embeddings and some metadata about the codebase might be stored, but not the actual code itself. Additionally, file contents are temporarily cached on Cursor's servers to improve performance, and this cached data is encrypted using client-generated keys that are only active for the duration of the request.

‍Self-Hosting and VPCs‍

Cursor does not currently offer options for users to self-host its primary AI models or utilize Virtual Private Clouds (VPCs) for enhanced security. The infrastructure for Cursor runs exclusively on Amazon Web Services (AWS) and incorporates enterprise-grade security measures, including SOC 2 Type II compliance.

There are community-developed methods for integrating locally hosted Large Language Models (LLMs) with Cursor. This typically involves setting up a local server that emulates the OpenAI API format and then configuring Cursor to use this local server by overriding the OpenAI API key in the settings. Tools like Ollama or LM Studio can facilitate the running of LLMs locally.

Use of Code for Training‍

Cursor's policy on using user code for model training is contingent upon the "Privacy Mode" setting. When Privacy Mode is enabled, Cursor guarantees that user code is not stored in plaintext on their servers or by any subprocessors, and it is not used for training their models or any third-party models.

If Privacy Mode is disabled, Cursor may collect telemetry and usage data, including prompts, editor actions, and code snippets, which they use to evaluate and improve their AI features. Cursor has a zero data retention agreement with major LLM providers like OpenAI and Anthropic when Privacy Mode is enabled. 

Pricing

Team Plans‍

The team plan for Cursor is the "Business" plan, which costs $40 per user per month. This plan includes all the features offered in the Pro plan, along with additional features designed for team use, such as organization-wide enforcement of privacy mode, centralized team billing, an administrative dashboard with usage statistics, and support for SAML/OIDC Single Sign-On (SSO).

‍Individual Plans‍

Cursor offers an individual plan called "Pro," which is priced at $20 per month. The Pro plan includes all the features of the free "Hobby" plan, plus unlimited code completions and a greater allowance of fast premium requests per month. Additionally, Cursor offers a free "Hobby" plan that includes a two-week trial of the Pro features, along with a limited number of code completions and slow premium requests each month.

Free Trial‍

Cursor provides a free trial of its Pro plan to all new users for a period of two weeks. This trial period allows users to experience the full set of features available in the Pro subscription, including unlimited completions and a generous allowance of fast premium requests. 

Impact

Developer Productivity‍

The impact of Cursor on developer productivity is reported to be significant and largely positive. Many users have experienced substantial gains in their coding speed and overall efficiency, with some claiming a productivity increase of at least 2x compared to using tools like GitHub Copilot. This improvement is attributed to Cursor's ability to intelligently predict code completions, often anticipating the developer's needs and suggesting entire lines or blocks of code. The natural language editing feature also contributes to faster development by allowing users to describe coding tasks in plain English. Studies and user testimonials suggest that Cursor can lead to a considerable reduction in the time spent on routine coding tasks, freeing up developers to focus on more complex problem-solving and higher-level design.

Code Quality & Accuracy‍

Cursor generally has a positive impact on code quality and accuracy. Features such as smart rewrites can automatically correct errors and improve code, while intelligent code suggestions based on project context help developers write more consistent and accurate code. Cursor's ability to perform code reviews and suggest refactoring can contribute to cleaner, more efficient, and maintainable codebases. 

SDLC Phases Impacted‍

Cursor has the potential to influence various stages of the software development life cycle (SDLC). Its primary impact is on the coding and development phase, where it assists with code generation, completion, and editing. It also plays a role in understanding existing code by providing codebase knowledge and chat-based explanations. Additionally, Cursor can aid in debugging by identifying errors and suggesting fixes, and in refactoring through intelligent code refinement and smart rewrites. 

Suggestion Accuracy & Acceptance‍

The suggestions provided by Cursor are generally considered to be highly accurate. Users have frequently praised the tool's ability to anticipate their coding intentions, with the tab completion feature sometimes exhibiting an almost uncanny level of accuracy. Cursor is also noted for its ability to suggest relevant multi-line edits and to identify inconsistencies in existing code, offering appropriate corrections. However, the accuracy of suggestions can be influenced by the complexity of the coding task and the specific context of the project. Some users have experienced instances where the AI struggled with more intricate or less common scenarios, leading to suggestions that were not entirely accurate or relevant. 

Summary

Cursor stands out as a compelling AI-powered code editor that offers a rich set of features designed to enhance developer productivity and code quality. Built upon the familiar foundation of VS Code, it provides a seamless transition for many developers while integrating advanced AI capabilities that can streamline various aspects of the software development lifecycle.

Its strengths lie in its intelligent code completion, natural language interaction, robust Agent mode for autonomous task completion, and deep understanding of project context. The broad integration ecosystem, supporting numerous platforms, languages, frameworks, and LLM providers (including the option to use custom API keys), offers significant flexibility for diverse development teams.

Recommendations

• Pilot Program: Initiate a pilot program with a diverse group of engineers to evaluate Cursor's impact on their specific workflows, projects, and technology stacks. This will provide valuable, firsthand insights into its suitability for your organization.
• Privacy Mode: Emphasize the importance of enabling "Privacy Mode" for all projects, especially those with sensitive data or strict security requirements, to ensure zero code retention and prevent code usage for model training.
• .cursorrules Configuration: Encourage teams to invest time in creating and refining .cursorrules files for their projects. This will help align Cursor's suggestions with your team's coding standards, architectural patterns, and best practices, leading to more consistent and maintainable code.
• LLM Model Exploration: Encourage experimentation with the various supported LLM models to identify the best options for different types of coding tasks, considering factors like performance, accuracy, and cost. If applicable, explore the use of custom API keys to optimize costs based on your organization's existing agreements with LLM providers.
• Training and Best Practices: Provide training and resources to your engineering team on how to effectively utilize Cursor's features, including Agent mode, chat functionalities, and context management. Highlight the importance of critically reviewing and thoroughly testing all AI-generated code.
• Feedback and Monitoring: Establish a channel for engineers to provide feedback on their experiences with Cursor. Monitor metrics such as usage patterns, perceived productivity gains, and the accuracy and acceptance rate of suggestions to gauge the tool's overall effectiveness and identify areas for improvement in its use.