Why Developers Are Ditching Cursor: A Look at Privacy-Focused AI Code Editor Alternatives

A recent discussion among developers highlights a significant shift in preferences for AI-powered coding tools, driven largely by privacy concerns and the performance of underlying AI models. Many are actively seeking alternatives to the popular AI-native editor, Cursor, expressing significant reservations about its evolving policies and features.

The Move Away from Cursor

The primary catalyst for developers leaving Cursor is a recent change to its data-sharing policy. Users reported that upon reinstallation, the editor now requires agreement to data and code sharing by default, with the option to disable it later being unclear or hard to find. This opt-out approach, a change from previous opt-in choices, was a major red flag for those handling private or proprietary code. One user noted they uninstalled the application immediately after being unable to find the setting to disable sharing post-installation.

Beyond privacy, Cursor's 'agent mode' received criticism for its unreliability. Developers found it would either 'overshoot' by overcomplicating code or miss the context entirely. Worse, it was reported to sometimes refactor destructively, deleting important developer comments or other parts of the codebase.

Top Alternatives Being Considered

Developers in the conversation shared their current setups and recommendations, focusing on tools that prioritize privacy and leverage powerful, modern AI models.

• Claude Code: This tool is highly recommended for its flexibility and the strength of Anthropic's models, particularly Sonnet. A key advantage is its IDE-agnostic nature; developers use it in a terminal alongside their preferred editor (like VS Code or JetBrains IDEs) for specific tasks. Common use cases include generating command-line flags or refactoring functions into different packages. The main drawback mentioned is its relatively small context size, which can be a hurdle when debugging complex errors in large codebases.

• Continue.dev: For those seeking a tightly integrated yet private solution, continue.dev emerged as a strong contender. It's an open-source VS Code extension that puts privacy first. Its architecture allows developers to connect to various LLM APIs or even run local models on their own machine, ensuring that their code never leaves their control.

• GitHub Copilot: While a foundational tool in the AI coding space, some developers feel Copilot's models are beginning to show their age. It's still valued for boilerplate autocompletion within VS Code and JetBrains IDEs. However, when it comes to generating novel or complex code, users find that newer models from providers like DeepSeek, Google (Gemini), and Anthropic (Claude) now offer significantly better performance.