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To protect private code, configure four separate boundaries: what an assistant sends to its model provider, whether conversations or tasks are retained, whether they can be used for training, and which repositories or tools an agent can access. A training opt-out does not keep code on your device or guarantee that it is never stored.
The right settings depend on the product, account plan, model route, and whether you use an editor, a cloud agent, or an API. The controls below reflect official documentation and policies available as of October 13, 2026; confirm the current settings for your account before relying on them.
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What do you need to protect?
“Keep my code private” can mean several different things. Treat these as separate questions rather than relying on a single privacy label:
- Transmission: Does the tool send prompts, code snippets, repository context, or other information to a model provider? An editor extension or coding assistant is not necessarily local-only.
- Retention: Are prompts, outputs, code, or agent environments stored, and for how long? A policy against training does not by itself answer this.
- Training: Can interactions or task data be used to improve models? The answer may depend on plan, account settings, or a separate control.
- Access and action: Which repositories, files, integrations, and tools can an agent read or change? Limiting what it can access is distinct from limiting what a provider retains.
For example, OpenAI’s API policy says API data is not used for model training by default, while separate controls address abuse-monitoring retention. Cursor describes both transmission to model providers and privacy-mode and retention considerations. Neither fact means every request stays on the developer’s machine.
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Start with the account and execution path
Before changing settings, identify how the person is signed in and where the assistant runs. A personal subscription, a managed organization account, an API key, an editor completion feature, a command-line session, and a cloud agent may be governed by different settings or providers. Record these details for each developer or workspace:
- Product and plan, including whether the account is personal or organization-managed.
- Which surface is in use: editor suggestions, chat, CLI, cloud agent, or API.
- Whether requests use the product’s default model route or a user-supplied API key.
- Which repositories and integrations are enabled for the assistant or agent.
This inventory matters because organization policy can override or constrain individual choices, and a plan or provider change can change which policy applies. Recheck privacy settings after changing account, plan, model, API key, or cloud features.
Compare the documented controls
The table summarizes what the official documentation establishes as of October 13, 2026. “Not established here” means the cited product documentation identified in the sources does not provide enough detail to make a reliable general claim; it is not a guarantee that no control exists.
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|---|---|---|---|
| GitHub Copilot Free, Pro, Pro+, and Max | GitHub says interactions are used for training beginning April 24, 2026 unless the user opts out in Copilot settings. | Do not treat the training preference as a transmission or retention control. The cited policy establishes the training treatment, not a universal no-storage promise. | Organization policies govern privacy and feature availability. Agent access depends on repositories enabled for Copilot cloud agent. |
| GitHub Copilot Business and Enterprise | GitHub says these plans are excluded from the 2026 training-policy change; their data is protected by its Data Protection Agreement. The individual training setting is not displayed for these plans. | The cited sources do not establish that every interaction remains local or is never retained. | Organization administrators manage policies and agent availability, including repository scope. |
| Cursor | Privacy Mode addresses whether code is used for training. Cursor says it is enabled by default for Teams and Enterprise and can be enforced by administrators. | Cursor says prompts and code context are sent to providers when AI features are used. Some models are outside its zero-data-retention arrangements; a user’s own API key follows the provider’s policy. | Admins can enforce Privacy Mode. Cloud Agents use isolated virtual machines and temporarily store encrypted repository copies while a run is active. |
| ChatGPT individual Free, Plus, and Pro; Codex | “Improve the model for everyone” can be disabled for new conversations and Codex tasks. Codex has a separate “Include environments” control for training on full environments. | Training exclusion is not a zero-retention guarantee. | The cited sources establish these account controls but do not establish a single repository permission model for every Codex execution surface. |
| ChatGPT Business, Enterprise, and Edu; OpenAI API | OpenAI says content is not used to improve models by default. | API retention is governed separately. Eligible organizations may apply for Modified Abuse Monitoring or Zero Data Retention, each with eligibility and feature limitations. | Approved API controls are configured by administrators in organization or project data settings. Confirm which controls are approved and apply to the particular project. |
| Claude Code | Not established here: the official data-usage page does not provide readable policy details in the documentation reviewed for this article. | Not established here: confirm the current account or deployment terms rather than assuming a training or retention default. | Official permissions documentation describes allow/deny rules and permission modes for tool use. These limit agent capability; they do not settle data-use or retention policy. |
Configure GitHub Copilot by plan
Personal Free, Pro, Pro+, or Max accounts
- Sign in to the GitHub account that actually uses Copilot, then open Copilot settings.
- Find the training preference labeled “Allow GitHub to use my data for AI model training”.
- Choose Disabled if you do not want eligible interactions used for training.
- Check the setting again if the plan or account identity changes. The policy is plan-specific, and a personal account is not automatically governed by an employer’s organization settings.
GitHub’s March 25, 2026 announcement says that, starting April 24, 2026, interaction data—including inputs, outputs, code snippets, and associated context—from Copilot Free, Pro, Pro+, and Max users is used to train and improve models unless users opt out. The announcement’s quoted description named Free, Pro, and Pro+; GitHub’s later individual-subscriber documentation also identifies Max in the affected group. The operational setting is the account-level training dropdown in Copilot settings.
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That preference addresses training use, not whether a request is transmitted to a provider or whether it is retained for another purpose. Do not interpret “Disabled” as a local-only setting.
Business and Enterprise accounts
GitHub says Business and Enterprise users are not affected by the April 2026 change and that customer data is protected by its Data Protection Agreement. The individual training dropdown is not shown for these plans. Administrators should review organization-level Copilot policies for privacy and feature availability rather than asking users to look for a setting that may not appear on their account.
Public-code matching is a separate decision
Copilot’s public-code matching control concerns whether suggestions matching public GitHub code are allowed or blocked, where that behavior is supported. It is an output-matching choice, not a substitute for the training preference and not a control over prompt transmission.
Configure Cursor without confusing privacy mode with local processing
- Open Cursor Settings.
- Select General.
- Turn Privacy Mode on.
- If Cursor is used by a team, ask an administrator to confirm whether the organization enforces the mode. Cursor says Privacy Mode is enabled by default for Teams and Enterprise and can be enforced by admins.
Cursor explicitly says it sends prompts and code context to model providers, including OpenAI, Anthropic, and Google, when AI features are used. Privacy Mode is therefore not evidence that requests stay on the device; Cursor describes it as preventing code from being used for training. Review transmission and retention separately.
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Check the model route and API key
Cursor says some models fall outside its zero-data-retention arrangements and require administrator approval for team, enterprise, or privacy-mode use. A product-wide privacy label does not establish that every available model has the same retention terms. Check the exact model and route before enabling it. If a developer supplies their own API key, the provider’s privacy policy governs that route; Cursor’s setting does not replace it.
Review cloud-agent runs separately
Cursor’s enterprise governance documentation distinguishes ordinary language-model requests from Cloud Agents. A cloud agent needs repository access during its run. Cursor describes isolated virtual machines and encrypted repository copies stored temporarily while the agent is active and deleted after completion. Because the agent needs the code to perform the task, enabling Privacy Mode does not eliminate that cloud-agent data flow.
Configure ChatGPT and Codex data controls
Individual ChatGPT Free, Plus, or Pro
- In ChatGPT, open Settings > Data controls.
- Turn off Improve the model for everyone if you do not want new conversations and Codex tasks used to train models.
- Alternatively, use the OpenAI Privacy Portal to change the training preference.
OpenAI says either control excludes new conversations and Codex tasks from training. This is a training choice, not a declaration that no data is transmitted or stored.
Codex environment data
Codex provides a separate Include environments setting for training on full environments. Changing the ChatGPT setting or Privacy Portal preference does not change this separate control. If full environments contain private source code or configuration, inspect this setting independently rather than assuming the conversation preference covers it.
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Business, Enterprise, Edu, and API
OpenAI says ChatGPT Business, Enterprise, and Edu content, as well as API content, is not used to improve models by default. For API use, training and retention are distinct: eligible organizations can apply for Modified Abuse Monitoring or Zero Data Retention, then configure approved controls in organization or project data settings. These programs have eligibility rules and feature limitations, so do not promise that every account or request qualifies for zero retention.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Limit agent access and actions
Repository scope is a practical security boundary: an agent should not receive access to code it does not need for the task. Apply least privilege to each cloud or third-party agent, then review integrations separately. A broad organization connection can expose more than the single repository visible in an editor.
For Copilot organization administrators
Use the organization’s Copilot settings to govern privacy and feature availability, including whether coding agents are enabled. GitHub says enabled coding agents can access repositories enabled for Copilot cloud agent. Review that repository list as an explicit access decision; do not assume that an agent is restricted to whichever repository a developer happens to have open.
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Decide whether the task needs a cloud agent at all, and grant access only to the repository required for the run. Account for the temporary encrypted repository copy used while a run is active. That documented lifecycle is specific to the cloud-agent flow and should not be generalized into a claim that all Cursor requests follow the same storage path.
For Claude Code
Use the official permissions documentation to configure allow/deny rules and permission modes. Treat these as controls on what the agent can do and which tool use requires approval. They are separate from the account’s data-use terms: permission settings alone do not establish whether code is retained or used for training.
Use a safe configuration sequence
- Map the path. Identify product, account owner, plan, surface, model, and whether requests use a product route or a personal API key.
- Set training preferences. Change the applicable Copilot or ChatGPT/Codex control. For managed plans, confirm the organization policy instead of assuming an individual setting applies.
- Inspect retention terms. In particular, distinguish OpenAI API training defaults from abuse-monitoring retention, and Cursor Privacy Mode from provider- or model-specific retention exceptions.
- Constrain access. Review repositories enabled for each agent, available integrations, permissions, and approval requirements for actions that may expose or change data.
- Minimize prompt content. Do not paste credentials or unrelated sensitive files into prompts. Send only the context needed for the task.
- Recheck after changes. Revisit the settings after a plan or account change, a new model, enabling a cloud feature or extension, or switching to a personal API key.
The official sources establish that code context can be transmitted, but they do not establish one identical file-exclusion control across these products. Verify the current product-specific exclusion behavior before relying on it. If you need to validate how a configuration behaves, use non-sensitive sample data rather than secrets or proprietary code.
Common configuration mistakes
- Assuming training opt-out means no transmission. It only answers the training question. Check the product’s provider path separately.
- Assuming “not used to train” means “never retained.” Retention and deletion are separate policy controls; API abuse-monitoring controls, for example, are documented separately from the training default.
- Treating an organization account like a personal one. Administrators may govern features and privacy centrally, and some personal settings do not appear on managed plans.
- Assuming every model has the same protections. Cursor documents model-specific retention exceptions and different handling for user-supplied API keys.
- Enabling an agent without reviewing its repository scope. A cloud agent may access repositories enabled for it, not merely the current editor context.
- Using permission modes as a data policy. Agent allow/deny rules constrain actions; they do not establish training or retention behavior.
- Assuming a tool has a universal file exclusion rule. The documented evidence does not establish a common exclusion control across all four products. Confirm the exact setting for the product and feature in use.
When the policy is unclear
For Claude Code, the official data-usage page is not sufficient here to establish detailed training or retention defaults. Check the current page and the terms for the relevant account or deployment before entering private source code. The permissions documentation can still help constrain tool access, but it cannot answer those data-policy questions.
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