The Unsexy Way to Deploy an AI Agent

说明与用途

使用 GitLab CI/CD 自动化 AI 工作流：零重写，访问仓库和 Git 历史、秘密和调度器。

问题

Deploying AI workflows that rely on local repository context to the cloud without manual triggering or excessive infrastructure changes.

结果

Zero rewrite of the existing workflow; the CI/CD pipeline automatically provides repository context, Git history, secrets, and scheduling, enabling fully automated cloud execution.

工作流

• 1. Store the AI workflow in a GitLab repository.
• 2. Configure a scheduled CI pipeline to trigger the workflow at desired intervals.
• 3. The CI runner checks out the repository and accesses Git history automatically.
• 4. The pipeline runs the workflow scripts, using available CI secrets and dependencies.
• 5. The workflow produces an investigation report and exits.
• 6. Repeat on schedule without manual intervention.

证据

I built an internal investigation agent that periodically picks up newly triaged engineering issues, investigates the relevant codebase and Git history, and produces an investigation report.

来源

Instead, I put the existing workflow behind a scheduled CI pipeline.

来源

Zero rewrite.

来源

The CI runner already has most of this. It can: check out the repository, access Git history, run scripts, access CI secrets, install dependencies, run containers, call external APIs.

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