The Code Intelligence & Automation AI Agent Team is a specialized multi-agent system built to streamline the entire software development lifecycle. Powered by GitHub as the central source of truth and orchestrated through n8n, the team coordinates AI and automation tools to handle repetitive, high-friction tasks that slow down developers.

The workflow begins with GitHub webhooks triggering n8n workflows whenever pull requests or code pushes occur. Using the OpenAI API, the Planner agent analyzes changes and generates a step-by-step improvement plan. The Author agent then drafts structured patches, drawing on Sourcegraph for precise code context, and commits safe changes through GitHub branches. The Reviewer agent enforces quality standards with Semgrep scans, coding style checks, and automated test executions via GitHub Actions. Test coverage and results are tracked using Codecov, ensuring changes meet reliability thresholds before advancing.

Beyond code quality, the Doc agent leverages LLMs to update Notion or inline repository documentation, while the Tester agent adds or extends unit tests to maintain strong coverage. When a pull request is ready, Vercel automatically generates preview deployments, giving developers and reviewers a live environment to validate changes. Slack serves as the human-in-the-loop interface, with agents posting summaries, PR status, and action buttons for applying or rejecting proposed patches. Issues and labels are managed directly in GitHub Issues, keeping the development backlog in sync with AI-driven contributions.

All activity is logged and correlated in Airtable, providing an audit trail of prompts, decisions, and outcomes for transparency and iteration. Guardrails such as GitHub branch protection rules ensure that agents cannot merge directly to main; instead, they propose safe pull requests that humans can approve or allow to auto-merge only if all checks are passed and the change falls within low-risk categories.

By combining these tools into a cohesive system, the Code Intelligence & Automation AI Agent Team reduces developer overhead, shortens review cycles, and improves consistency across large codebases—allowing human engineers to focus on creative problem-solving rather than repetitive chores.