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Continue and Cline are the strongest starting points when code must stay under your team’s control. Continue documents offline and self-hosted model workflows, while Cline supports local runtimes or bring-your-own-key (BYOK) providers and requires approval before every agent action. Amazon Q Developer Pro is a good fit for AWS-governed teams that can accept a managed service and need documented limits on training use, regional controls and selected customer-managed encryption. Cursor can be hardened with Privacy Mode and enterprise controls, but it still sends requests to Cursor’s servers and does not offer a self-hosted server deployment.
The right choice depends on your security boundary, not on an assistant’s autocomplete quality alone. Decide whether cloud processing is allowed, which model provider may see source code, how long prompts and repositories may be retained, where processing may occur, and what an agent can do without approval.
What “private” must mean for a coding assistant
For a sensitive codebase, privacy is a set of independently controlled properties rather than a single switch. A tool can exclude your code from model training and still transmit prompts to a hosted provider. It can run in your virtual private cloud (VPC) and still retain agent transcripts. It can be open source while depending on a model API outside your approved region. Evaluate each property separately.
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|---|---|---|
| Data path | What leaves the workstation or build network? | Prompts, retrieved files, diffs, telemetry and credentials can each expose sensitive information. |
| Retention | Are requests, repositories, chat history or logs stored, and for how long? | Storage creates a second copy that must be governed, deleted and discovered in an incident. |
| Training and service improvement | Can the provider use your content to improve models? | A no-training promise reduces one risk but does not make transmission or retention disappear. |
| Deployment location | Is the service SaaS, privately connected, self-hosted, local, or offline? | Location determines which network boundaries and jurisdictions apply. |
| Model control | Can you select a local, self-hosted or approved provider model? | Model choice determines where source code and prompts are processed. |
| Identity and audit | Are SSO, role-based access control (RBAC), audit logs and centralized policy available? | Security teams need to know who used the assistant, what it accessed and what it changed. |
| Agent permissions | Can the assistant edit files, execute commands, browse the web or access secrets? | Action scope is often a larger practical risk than autocomplete. |
| Regional and contractual controls | Which regions, data-processing terms and regulated-workload agreements apply? | Processing geography and contract language can be mandatory for regulated systems. |
Do not describe any product as universally “fully private.” A defensible statement names the model provider, retention behavior, telemetry, processing region and agent-storage behavior for the exact plan and features you will use.
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Private alternatives at a glance
| Option | Deployment and data boundary | Governance and workflow | Best fit | Main limitation |
|---|---|---|---|---|
| Cursor | Managed cloud. Requests send code data to Cursor servers; Cloud Agents require repository storage. Privacy Mode excludes code from training by Cursor or other model providers. | Privacy Mode, enforced organization controls, repository blocklists, customer-managed encryption keys (CMEK) and private connectivity are documented. | Teams that accept a managed service but want strong organization-level controls. | No self-hosted server deployment is offered, so it is not an on-premises or air-gapped option. |
| Continue | Open source for VS Code and JetBrains. Documentation covers running without internet and self-hosting a model. | Agent, chat, edit, autocomplete and CLI workflows; your team operates the model host and surrounding controls. | Organizations that need the security boundary to remain under their control. | Hosting, patching, capacity, model evaluation and incident response become your responsibility. |
| Cline | Editor and terminal agent with local runtimes, open-weight models and BYOK options. | Every action requires explicit approval. Enterprise features include SSO, RBAC, model and tool controls, remote configuration and observability integrations. | Teams that want powerful file, command and browser actions behind a human gate. | BYOK is not automatically offline; the selected provider may still receive code and prompts. |
| Amazon Q Developer | Managed AWS service. Storage and processing vary by feature, tier and region. | Pro-tier content is not used for service improvement or model training. TLS 1.2 or higher protects data in transit; selected Pro features support customer-managed KMS keys. | AWS-centric organizations needing a governed cloud assistant and code-security reviews. | You must verify feature-specific storage, regional processing and contract terms; it is not a general air-gapped solution. |
Cursor: a hardened cloud baseline, not self-hosting
Cursor remains a reasonable choice when your policy permits a hosted coding assistant and the security team can accept Cursor’s service architecture. Its Privacy Mode statement says that code is never used for training by Cursor or other AI model providers when the mode is enabled. That addresses training use, but it does not mean that code stays on the developer’s machine: Cursor’s security documentation says AI requests send code data to Cursor servers.
Controls Cursor documents
- Privacy Mode: a setting intended to prevent submitted code from being used for training by Cursor or other model providers.
- Enforced organization controls: administrators can require privacy-related settings rather than relying on each developer to configure them.
- Repository blocklists: teams can prevent selected repositories from being used with the assistant.
- CMEK: customer-managed encryption keys are available for supported enterprise scenarios.
- Private connectivity: documented options can reduce exposure on the network path to the service.
What Cursor cannot provide
Cursor states that it does not offer a self-hosted server deployment. That rules it out when policy requires the model gateway, request handling and service storage to run inside your own infrastructure. It also means Privacy Mode should not be presented as an offline or air-gapped mode.
Cloud Agent consideration
Cloud Agents require repository storage. Treat that as a separate data-flow decision from ordinary editor requests: determine which repositories may be stored, how long they remain available, who can retrieve agent artifacts and how deletion is enforced. Block especially sensitive repositories if the workflow cannot meet their storage policy.
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Continue: the clearest path to offline or self-hosted operation
Continue describes itself as an open-source AI code assistant for VS Code and JetBrains. Its documented feature set includes agent, chat, edit, autocomplete and CLI workflows. More importantly for sensitive environments, its documentation includes guides for running without internet access and for self-hosting a model.
Why Continue fits a controlled boundary
- Open implementation: security engineers can inspect how the extension and configuration are deployed and can pin approved versions.
- Local or self-hosted models: the model endpoint can be placed on developer hardware or infrastructure controlled by the organization, subject to the model’s own license and requirements.
- Offline workflow: a no-internet setup can keep prompts, retrieved files and responses inside an isolated network when the chosen model and dependencies are available locally.
- Broad interaction modes: developers can use autocomplete for low-risk suggestions and reserve agent or edit capabilities for repositories with appropriate controls.
Operational responsibilities
Self-hosting moves responsibility to your team. You must secure the model server, authenticate clients, restrict which projects can call it, patch the operating system and inference stack, monitor capacity, back up configuration safely and remove logs that contain source code. The model host may also emit telemetry unless you disable or control it. Open source does not by itself prove that every dependency is suitable for an air-gapped environment.
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Practical Continue deployment pattern
- Choose an approved model whose license permits internal use and whose hardware requirements fit the development environment.
- Deploy the model endpoint on an isolated host or approved internal network segment; expose only the API required by the IDE and CLI clients.
- Configure Continue to use that endpoint and disable any fallback provider that would send requests to the public internet.
- Apply repository and file-pattern rules so secrets, production credentials and generated artifacts are not added to context.
- Log authentication events and high-level usage for audit, while preventing source-code payloads from entering general-purpose logs.
- Test the setup with network egress disabled and confirm that autocomplete, chat, edits and agent actions fail closed rather than silently switching providers.
Cline: agent capability with an explicit approval gate
Cline is an editor and terminal agent that can read and write files, run commands and use a browser. Its documentation states: “Every action requires your explicit approval. You’re always in control.” That interaction model is valuable when the principal risk is an autonomous change or command rather than a passive completion.
Data and model choices
Cline documents open-weight models, local runtimes and BYOK. A local runtime can keep inference on an approved machine. BYOK lets an organization select a provider under its own account and contract, but it still sends prompts and code to that provider unless the provider is hosted locally or within the organization’s approved boundary. Verify retention, training exclusions, region and telemetry for the specific key and model.
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Enterprise controls
Documented enterprise capabilities include SSO, RBAC, model and tool controls, remote configuration and observability integrations. Use these to separate developers who may use read-only assistance from those allowed to approve shell commands, browser access or broad file edits. Central configuration is preferable to relying on a local setting that a developer can change.
Approval policy that scales
- Allow automatic read-only operations such as listing files or searching code where policy permits.
- Require approval for writes outside the current task directory, dependency changes, network access and every shell command that can alter state.
- Block access to credential files, CI secrets, production configuration and private keys at the editor and operating-system levels.
- Record the proposed action, approver identity, result and resulting diff without storing more source than your retention policy allows.
- Use separate credentials for the agent and the developer so revoking agent access does not revoke the person’s normal account.
Amazon Q Developer: AWS-governed cloud assistance
Amazon Q Developer Pro is suited to organizations that already use AWS identity, regions and key-management controls and can accept a managed service. AWS documents that Pro-tier code content is not used for service improvement or model training. That is a meaningful contractual and product distinction, but it does not remove the need to examine where each feature stores and processes content.
Security and review capabilities
Amazon Q can review code for vulnerabilities, secrets, infrastructure-as-code misconfiguration, quality issues, deployment risk and software-composition concerns. Those checks can complement existing scanners, but they should be evaluated against your approved data-flow and retention requirements before enabling them on restricted repositories.
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Encryption and regional behavior
AWS documents TLS 1.2 or higher for data in transit. Customer-managed AWS KMS keys are available for selected Pro features, not necessarily every workflow. AWS also states that content storage and processing vary by feature, tier and region. Confirm the exact region, storage location, deletion behavior and cross-region processing for code chat, reviews, generated artifacts and any agent-like feature you plan to use.
When Amazon Q is the pragmatic choice
Choose it when centralized AWS identity, policy and audit integration outweigh the need to run inference locally. It is not a substitute for an air-gapped deployment, and “AWS-hosted” should not be interpreted as “all processing occurs in your account.” Procurement should obtain feature-level documentation and contractual terms for the regions in which your developers work.
Choose by threat model, not by feature count
Air-gapped or no-internet development
Start with Continue’s documented offline and self-hosted model path, or Cline with a genuinely local runtime. Disable network egress and verify that the assistant still works. A BYOK configuration pointing to a public API does not satisfy an air-gap requirement, even if the key belongs to your organization.
Cloud is allowed, but code must not train models
Cursor Privacy Mode and Amazon Q Developer Pro both document exclusions from model training, but their data paths differ. Cursor still sends requests to Cursor servers, while Amazon Q’s storage and processing depend on the feature, tier and region. Record the exact setting or Pro entitlement in your control evidence.
AWS-regulated environment
Amazon Q may reduce integration work when your identity, logging and key-management standards are already AWS-based. Verify regional processing and selected-feature KMS support before approving a repository class.
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Agent actions require human control
Cline’s explicit approval model is the clearest documented fit. Combine it with operating-system permissions, repository isolation and network policy; an approval dialog cannot compensate for an agent that can read every secret on a workstation.
Teams that want an open, adaptable stack
Continue offers the broadest control over the client and model-hosting arrangement. Budget for internal ownership of reliability, upgrades, model evaluation and support.
Migration plan from Cursor
- Classify repositories. Mark which projects contain regulated data, proprietary algorithms, credentials, customer information or export-controlled material.
- Capture the current Cursor flow. Document whether Privacy Mode is enforced, which repositories are blocklisted, whether Cloud Agents are used and what organization controls are active.
- Pick a pilot boundary. Use a non-production repository that represents your language, build system and dependency patterns without exposing restricted data.
- Test one local path and one managed path. For example, evaluate Continue with a self-hosted model and Amazon Q Pro or Cline BYOK under the proposed contract. Keep model, region and retention settings explicit.
- Run egress and retention tests. Inspect firewall logs, DNS requests, provider dashboards and service deletion controls. Confirm that disabled features cannot silently send context elsewhere.
- Compare developer workflows. Measure whether autocomplete, chat, edits, CLI use, code review and agent approvals cover the tasks your team actually performs. Do not substitute unverified productivity claims for observed acceptance criteria.
- Roll out by policy tier. Give the most restrictive repositories a local or self-hosted configuration, permit approved cloud workflows for lower-risk projects and revisit classifications as the system changes.
Controls to require before production use
- Identity: SSO, MFA, RBAC and immediate offboarding for users and service accounts.
- Repository scope: allowlists or blocklists, workspace boundaries and protection against indexing parent directories.
- Secrets: secret scanning, credential-file exclusion and short-lived credentials unavailable to the agent.
- Network: private connectivity where supported, egress filtering and explicit denial of unapproved model endpoints.
- Actions: approval gates for writes, shell commands, browser use, dependency installation and network calls.
- Logging: audit events for sign-in, model selection, tool invocation, approvals and policy changes; avoid copying full source into broadly accessible logs.
- Encryption: documented encryption in transit and at rest, with customer-managed keys where the service and feature support them.
- Retention: written periods for prompts, responses, repositories, agent transcripts, telemetry and backups, plus a deletion procedure.
- Change management: review model, provider, extension and policy changes before they reach sensitive workspaces.
- Incident response: a way to revoke keys, disable the assistant, identify affected repositories and investigate stored prompts or artifacts.
Common privacy mistakes and fixes
Confusing no-training with no-disclosure
A training exclusion governs model improvement. It does not prevent transmission to a service, temporary processing, support access or retained logs. Track those controls separately.
Assuming open source means air-gapped
Continue’s open-source client can be paired with an offline model, but an unreviewed extension, telemetry library or fallback endpoint can still create egress. Test the complete installed stack with outbound traffic blocked.
Treating BYOK as local inference
BYOK changes whose account pays for or governs a hosted API; it does not change where inference occurs. Require a local or internally hosted endpoint when the policy prohibits external processing.
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Giving an agent broad filesystem access
Approval prompts are useful only when the agent cannot quietly read unrelated secrets. Run it in a restricted workspace, use least-privilege accounts and exclude credential paths at multiple layers.
Ignoring feature-specific storage
Cloud chat, code review, repository indexing and agent execution may have different storage behavior. Obtain a data-flow statement for every enabled feature rather than relying on a product-wide label.
Failing to pin the model provider
A product may change its default provider or route requests through multiple providers. Configure an approved provider explicitly, monitor configuration drift and document the fallback behavior.
Procurement questions for security and legal teams
- Which exact prompts, files, diffs, embeddings, logs and metadata leave the workstation?
- Which subprocessors and model providers receive that data?
- Is content used for training or service improvement under the selected plan and feature?
- What are the retention and deletion periods, including backups and support systems?
- Which countries or regions process and store the data, and can that be restricted?
- Can the service operate through private connectivity or inside our VPC?
- Are customer-managed keys supported for the exact data and feature we will use?
- What SSO, RBAC, audit-log export, repository restrictions and administrator-enforced settings exist?
- Which agent tools can read files, execute commands, browse or access networks, and how are approvals enforced?
- Can administrators disable cloud fallback, telemetry and unapproved models?
- What notice and controls apply when the provider changes models, subprocessors or regions?
- Do our DPA, BAA or other regulatory agreements cover this workflow?
Verdict
Choose Continue when keeping inference and code inside your own boundary is the primary requirement. Choose Cline when you need an agent that can edit, run commands and browse but must obtain explicit approval for every action. Choose Amazon Q Developer Pro when AWS governance, documented no-training treatment for Pro code content and selected KMS controls fit your regional and contractual requirements. Keep Cursor as a cloud-governed baseline only when its server-side processing and repository-storage model are acceptable; Privacy Mode hardens that deployment but does not turn it into self-hosted or air-gapped software.
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