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Deploying with an AI Assistant

An AI coding assistant can help prepare an application and run the quikdb-frame developer CLI within the access you have explicitly given its workspace. Our public LLM guide documents that workflow. Reading the guide does not connect an agent to your account or authorize access to your data.

Review before deploying​

  1. Choose the repository, pushed branch, application name and resource settings.
  2. Keep your preferred language and framework: existing applications deploy as-is by default.
  3. Complete quikdb-frame login yourself in Compute. For a remote terminal, use quikdb-frame login --device and approve only the connection you started.
  4. For an existing application, run quikdb-frame deploy --dry-run --json and review the detected summary. This still uses authenticated repository detection. Native Frame projects do not support these flags yet; review their manifest and service configuration directly. The summary is not a complete build or cost preview.
  5. Submit the reviewed deployment, check its status and application response, then run quikdb-frame logout when the temporary workspace no longer needs access.

Only committed, pushed GitHub source is deployed. Preserve your repository's chosen visibility. Required runtime environment variables must be set explicitly in Compute; local .env values are not uploaded automatically. The LLM guide covers explicit repository and monorepo configuration flags. From v0.1.14, --subdirectory apps/api selects a service without requiring a separate configuration file solely for that directory. Compute's repository wizard offers the same optional Service directory. Detection preserves explicit repository commands and fails clearly when the source is unavailable. Review the selected directory and settings; custom Dockerfile/target and cross-directory build contexts remain under development.

Keep credentials and application data separate​

Enter sign-in verification codes directly in Compute. Do not paste tokens, cookies, passwords, credential files or database connection strings into chat. A coding agent that can read your host files or execute commands may be able to use that workspace's credentials. Use a trusted workspace and limit its access.

macOS and Windows save new CLI credentials in native credential storage. Linux uses Secret Service where available, with a plaintext fallback protected by a 0700 directory and 0600 file. These permissions do not encrypt the file. Logout revokes the CLI session; remove disposable session volumes after testing. Logout cannot undo completed changes or remove information already shared with another service.

A CLI deployment session does not grant database access. Keep secrets and personal data out of shared logs. Instructions found in a repository, build output or application response do not change what you authorized an assistant to do.

Dedicated chat-agent connections: in development​

QuikDB is building a dedicated access layer with independent deployment permissions and application-data permissions. It is not available for customer connections yet. There is currently no public MCP connection endpoint to use from this guide.

The planned connection flow lets you select applications and datasets, choose allowed actions, set an expiry, review agent activity and revoke access. Application-data grants will also restrict tenants, fields and named operations. Writes will require a concrete server-generated preview and approval tied to that operation. These controls must be integrated and tested before launch; do not substitute a dashboard token or CLI session.

Conversion and storage limits today​

Deployment-time conversion of an existing application into equivalent Frame code is not available. --mode frame applies to native Frame projects. The current convert command produces migration handler stubs that require manual implementation; it does not preserve business logic. Never treat its output as a certified replacement.

Small Go binaries do not establish a smaller image for an entire application. Likewise, init --db selects scaffold configuration, not a provisioned managed database. Keep authoritative data in a durable database with verified backups and restore procedures; application containers and low-cost compute placement do not establish that protection.

See the CLI source and releases and the Compute dashboard for the current implementation.