Cursor Privacy Mode: What It Does and Does Not Cover

Understanding the nuances of Cursor Privacy Mode is essential for developers working in regulated industries or on proprietary codebases. While AI code editors provide immense productivity gains, they introduce new questions about where your source code goes and who has access to it. This guide examines how the privacy settings in Cursor function, what they protect, and where the boundaries of that protection lie compared to other architectures.

What is Cursor Privacy Mode?

The primary purpose of Cursor Privacy Mode is to prevent the underlying AI models from being trained on your data. In its default state, many AI services reserve the right to use user prompts and code snippets to improve future versions of their models. When you enable Privacy Mode, the service explicitly states that your code and telemetry will not be used for training purposes.

This is a significant feature for professional developers. Without it, there is a theoretical risk that a proprietary algorithm or a secret API key could be reproduced in a suggestion for another user of the model. By opting into this mode, you are essentially requesting a zero-retention policy for training data.

What Privacy Mode Covers

When the toggle is active, the following protections are generally expected:

• Training exclusion: Your code snippets, file context, and chat history are not used to update the weights of the Large Language Models.
• Indexing limits: While the editor may still need to index your files locally to provide context to the AI, this index is meant for your use only.
• Prompt privacy: The specific instructions you give the AI are treated as transient data during the inference process.

These protections make the tool much more viable for enterprise use. Many companies have strict policies against contributing to public datasets, and this mode addresses that specific concern.

The Limits of Cloud-Based Privacy

It is important to understand that Cursor Privacy Mode does not mean your data never leaves your machine. Because Cursor relies on cloud-based models to generate code, your context must still be sent to a remote server.

Transit and Inference

Even with privacy settings enabled, your code is transmitted over the internet to reach the inference servers. These servers process the request and generate a response. While the data might not be stored for training, it is still processed in a memory space that you do not control. For some high-security environments, any transmission of source code to a third-party server is a violation of protocol.

Metadata and Telemetry

Privacy settings often distinguish between code content and telemetry. Telemetry includes data about how you use the app, such as which features you click or how long you spend in a session. While this is not your source code, it still creates a footprint of your activity in the cloud.

Comparison: Cloud-Based vs. Local-First AI

To choose the right tool, you must decide where your "trust boundary" sits. The following table compares the typical approach of cloud-connected editors like Cursor with local-first alternatives.

Deska: A Different Approach to Privacy

Deska offers a different architectural philosophy for developers who require absolute control over their environment. Instead of a centralized cloud service that monitors your workspace, Deska is a local-first desktop app available for Mac, Windows, and Linux.

The core of the local-first philosophy is that your files, terminal sessions, and code never leave your machine unless you explicitly send them somewhere. Deska provides an infinite canvas where you can arrange panels like terminals, code editors based on Monaco, and browsers.

Bring Your Own Keys (BYOK)

One way Deska ensures privacy is through its flexible inference model. For those who want the highest level of privacy, the lifetime tier allows you to bring your own API keys. This means you interact directly with providers like Anthropic or OpenAI, or even point the tools toward a local LLM server running on your hardware. There is no middleman inspecting the traffic between your editor and the model provider.

AI Agents on the Canvas

Deska allows you to run multiple coding agents side by side. You can have Claude Code running in one panel while OpenCode or Codex CLI runs in another. Because these are panels on an infinite canvas, you can see the output of every agent simultaneously. This transparency is a form of privacy in itself, as you see exactly what the agents are doing and what files they are accessing.

Remote Access Without the Cloud

A common challenge for local-first tools is how to handle mobile access. Most tools solve this by syncing your code to their servers. Deska uses a secure relay for its mobile app. Your phone and desktop pair directly. This allows you to monitor your terminals and continue work from your phone without exposing ports or storing your code in a third-party database.

When to Use Which Tool

Choosing between Cursor and Deska depends on your specific workflow needs and privacy requirements.

1. Use Cursor if you want a seamless, managed experience and are comfortable with your code being processed in the cloud under a non-training agreement.
2. Use Deska if you prefer a canvas based workspace where you can manage multiple coding agents and keep your data strictly on your local machine.
3. Use Deska if you need to run complex workflows with multiple terminals and browser widgets visible all at once while maintaining a local-first data policy.

FAQ

Does Cursor Privacy Mode store my code?

While the mode prevents your code from being used for training, the code is still sent to servers for processing during AI requests. Some logs may persist for a short period to ensure service reliability or to comply with legal requirements, depending on the provider terms.

Is local-first AI faster than cloud AI?

The speed of local-first AI depends on your hardware and the models you use. If you use a remote API key, the latency is similar to cloud-based editors. However, the data and storage remain under your control, which is the primary benefit of the local-first approach.

Can I use AI in Deska without an internet connection?

Yes, if you configure Deska to use a local inference engine like Ollama. This allows you to use the Ask Deska assistant and other agents entirely offline, ensuring that no data ever leaves your computer.

Get Started with Secure Coding

If you are looking for a workspace that respects your privacy while providing the power of modern AI agents, give Deska a try. You can download the app for free and start building on your own terms.

Download Deska for Mac, Windows, and Linux