docs/src/ai/ai-improvement.md
AI features in Zed include:
By default, Zed does not store your prompts or code context. This data is sent to your selected AI provider (e.g., Anthropic, OpenAI, Google, or xAI) to generate responses, then discarded. Zed will not use your data to evaluate or improve AI features unless you explicitly share it (see AI Feedback with Ratings) or you opt in to edit prediction training data collection (see Edit Predictions).
Zed is model-agnostic by design, and none of this changes based on which provider you choose. You can use your own API keys or Zed's hosted models without any data being retained.
Zed's Agent Panel can be used via:
When using Zed's hosted models, we require assurances from our service providers that your user content won't be used for training models.
| Provider | No Training Guarantee | Zero-Data Retention (ZDR) |
|---|---|---|
| Anthropic | Yes | Yes |
| Yes | Yes, see Service Terms sections 17 and 19h | |
| OpenAI | Yes | Yes |
| xAI | Yes | Yes |
When you use your own API keys or external agents, Zed does not have control over how your data is used by that service provider. You should reference your agreement with each service provider to understand what terms and conditions apply.
You can provide feedback on Zed's AI features by rating specific AI responses in Zed and sharing details related to those conversations with Zed. Each share is opt-in, and sharing once will not cause future content or data to be shared again.
Rating = Data Sharing: When you rate a response, your entire conversation thread is sent to Zed. This includes messages, AI responses, and thread metadata. If you don't want data persisted on Zed's servers, don't rate. We will not collect data for improving our AI features without you explicitly rating responses.
For conversations you have explicitly shared with us via rating, Zed may store:
If you do not rate responses, Zed will not store Customer Data (code, conversations, responses) related to your usage of the AI features.
Telemetry related to Zed's AI features is collected. This includes metadata such as the AI feature being used and high-level interactions with the feature to understand performance (e.g., Agent response time, edit acceptance/rejection in the Agent panel or edit completions). You can read more in Zed's telemetry documentation.
Collected data is stored in Snowflake, a private database. We periodically review this data to refine the agent's system prompt and tool use. All data is anonymized and stripped of sensitive information (access tokens, user IDs, email addresses).
Edit predictions can be powered by Zed's Zeta model or by third-party providers like GitHub Copilot.
Zed sends a limited context window to the model to generate predictions:
This data is processed transiently to generate predictions and is not retained afterward.
When using third-party providers like GitHub Copilot, Zed does not control how your data is handled by that provider. You should consult their Terms and Conditions directly.
Note: Zed's disabled_globs settings will prevent predictions from being requested, but third-party providers may receive file content when files are opened.
Zed does not collect training data for our edit prediction model unless the following conditions are met:
disabled_globsCertain files are always excluded from edit predictions—regardless of opt-in status:
{
"edit_predictions": {
"disabled_globs": [
"**/.env*",
"**/*.pem",
"**/*.key",
"**/*.cert",
"**/*.crt",
"**/secrets.yml"
]
}
}
Users may explicitly exclude additional paths and/or file extensions by adding them to edit_predictions.disabled_globs in their Zed settings file (how to edit):
{
"edit_predictions": {
"disabled_globs": ["secret_dir/*", "**/*.log"]
}
}
For open source projects where you've opted in, Zed may collect:
Collected data is stored in Snowflake. We periodically review this data to select training samples for inclusion in our model training dataset. We ensure any included data is anonymized and contains no sensitive information (access tokens, user IDs, email addresses, etc). This training dataset is publicly available at huggingface.co/datasets/zed-industries/zeta.
We then use this training dataset to fine-tune Qwen2.5-Coder-7B and make the resulting model available at huggingface.co/zed-industries/zeta.
Please see the Zed Terms of Service for more.